{
  "nbformat": 4,
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  "metadata": {
    "colab": {
      "name": "coronavirus_demo_colab.ipynb",
      "provenance": [],
      "toc_visible": true,
      "authorship_tag": "ABX9TyMEy9G8geLjB3XAo+nNInJI",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/jianxu305/nCov2019_analysis/blob/master/src/coronavirus_demo_colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IXMB4OWMP2ta",
        "colab_type": "text"
      },
      "source": [
        "# Understanding the Coronavirus Epidemic Data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I5sxaRViP-qG",
        "colab_type": "text"
      },
      "source": [
        "The novel coronavirus (previously named 2019-nCov, and later changed to COVID-19¹) is currently sweeping through China. It triggered a global health emergency², and claimed more than a thousand lives as of Feb 13, 2020³. People around the world are constantly bombarded with news, rumors, confusions, and panics.\n",
        "In order to help people better assess the situation, and to promote rational reactions, the epidemic data must be easily accessible to the general public. Many websites have been publishing some epidemic numbers in real time. For example, [Ding Xiang Yuan](https://ncov.dxy.cn/ncovh5/view/pneumonia), [Johns Hopkins CSSE](https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6), etc. These websites provide timely information to the general public, but they fall short of providing sufficient data for analysis. For example, answering any of the following simple questions will be very difficult or nearly impossible by using the websites mentioned above:\n",
        "\n",
        "* Q1. What is the number of confirmed cases in the past 7 days in the Hubei Province?\n",
        "\n",
        "* Q2. How do the daily new confirmed cases compare between the Guangdong Province and the Zhejiang Province?\n",
        "\n",
        "* Q3. What are the top 5 cities that have the highest death counts as of Feb 13, 2020?\n",
        "\n",
        "* (And much more …)\n",
        "\n",
        "In order to be able to analyze the data, a more convenient data set is necessary. The [DXY-2019-nCoV-Data](https://github.com/BlankerL/DXY-2019-nCoV-Data) GitHub project snaps the real time epidemic report from Ding Xiang Yuan several times a day, and saves it into a CSV file. But  this CSV file only contains snapshots of the data from the website. It's not easy to be used for analysis because the randomness of reporting times, and the changing reporting format.\n",
        "\n",
        "Therefore, this project [nCov2019_analysis](https://github.com/jianxu305/nCov2019_analysis) is created in GitHub. Its main purposes are the following:\n",
        "\n",
        "* Performs critical data cleaning\n",
        "\n",
        "* Provides a convenient structured data for users to explore and contribute\n",
        "\n",
        "* Analyzes some aspects of the coronavirus epidemic using this toolbox\n",
        "\n",
        "This GitHub project contains a Python Notebook to illustrate the basic usage. The notebook is in Google Colab for the convenience of readers. Following is a demo of the package."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wgXh764ygAxz",
        "colab_type": "code",
        "outputId": "53013cc8-bdce-41de-e401-7b94506069e2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        }
      },
      "source": [
        "! git clone https://github.com/jianxu305/nCov2019_analysis/\n",
        "\n",
        "import sys\n",
        "import os\n",
        "os.chdir('/content/nCov2019_analysis/src')\n",
        "\n",
        "sys.path.append('/content/nCov2019_analysis/src')"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'nCov2019_analysis'...\n",
            "remote: Enumerating objects: 153, done.\u001b[K\n",
            "remote: Counting objects: 100% (153/153), done.\u001b[K\n",
            "remote: Compressing objects: 100% (116/116), done.\u001b[K\n",
            "remote: Total 153 (delta 75), reused 95 (delta 37), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (153/153), 11.89 MiB | 19.30 MiB/s, done.\n",
            "Resolving deltas: 100% (75/75), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NhfmpLw_gk2s",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import utils   # some convenient functions\n",
        "\n",
        "%load_ext autoreload\n",
        "%autoreload 2"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8UZaqvtmKB7c",
        "colab_type": "text"
      },
      "source": [
        "## 1. Obtain Raw Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1LpP1df5hS5C",
        "colab_type": "code",
        "outputId": "147f9f48-25dc-4b20-ce63-c4664a9d19fd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "source": [
        "data = utils.load_chinese_data()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Last update:  2020-02-15 11:50:01.777000\n",
            "Data date range:  2020-01-24 to 2020-02-15\n",
            "Number of rows in raw data:  39953\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LiK6K65WhVnD",
        "colab_type": "code",
        "outputId": "e144a53d-b6e4-4d80-a189-353c90377b40",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 213
        }
      },
      "source": [
        "data.head(3)  # Check the data"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>province_name</th>\n",
              "      <th>city_name</th>\n",
              "      <th>province_confirmed</th>\n",
              "      <th>province_suspected</th>\n",
              "      <th>province_cured</th>\n",
              "      <th>province_dead</th>\n",
              "      <th>city_confirmed</th>\n",
              "      <th>city_suspected</th>\n",
              "      <th>city_cured</th>\n",
              "      <th>city_dead</th>\n",
              "      <th>update_time</th>\n",
              "      <th>update_date</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>广东省</td>\n",
              "      <td>深圳</td>\n",
              "      <td>1294</td>\n",
              "      <td>0</td>\n",
              "      <td>405</td>\n",
              "      <td>2</td>\n",
              "      <td>406</td>\n",
              "      <td>0</td>\n",
              "      <td>104</td>\n",
              "      <td>0</td>\n",
              "      <td>2020-02-15 11:50:01.777</td>\n",
              "      <td>2020-02-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>广东省</td>\n",
              "      <td>广州</td>\n",
              "      <td>1294</td>\n",
              "      <td>0</td>\n",
              "      <td>405</td>\n",
              "      <td>2</td>\n",
              "      <td>335</td>\n",
              "      <td>0</td>\n",
              "      <td>106</td>\n",
              "      <td>0</td>\n",
              "      <td>2020-02-15 11:50:01.777</td>\n",
              "      <td>2020-02-15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>广东省</td>\n",
              "      <td>东莞</td>\n",
              "      <td>1294</td>\n",
              "      <td>0</td>\n",
              "      <td>405</td>\n",
              "      <td>2</td>\n",
              "      <td>81</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>2020-02-15 11:50:01.777</td>\n",
              "      <td>2020-02-15</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  province_name city_name  ...             update_time  update_date\n",
              "0           广东省        深圳  ... 2020-02-15 11:50:01.777   2020-02-15\n",
              "1           广东省        广州  ... 2020-02-15 11:50:01.777   2020-02-15\n",
              "2           广东省        东莞  ... 2020-02-15 11:50:01.777   2020-02-15\n",
              "\n",
              "[3 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oSvxVO0AKPRU",
        "colab_type": "text"
      },
      "source": [
        "## 2. Data Processing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mPfUOpf8hX8y",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "daily_frm = utils.aggDaily(data)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MTcErc-RKgXX",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "b62e69ee-bf58-4d5e-e6fd-71890e9cfeae"
      },
      "source": [
        "daily_frm.tail()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>update_date</th>\n",
              "      <th>province_name</th>\n",
              "      <th>province_name_en</th>\n",
              "      <th>city_name</th>\n",
              "      <th>city_name_en</th>\n",
              "      <th>cum_confirmed</th>\n",
              "      <th>cum_cured</th>\n",
              "      <th>cum_dead</th>\n",
              "      <th>new_confirmed</th>\n",
              "      <th>new_cured</th>\n",
              "      <th>new_dead</th>\n",
              "      <th>update_time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>557</th>\n",
              "      <td>2020-02-15</td>\n",
              "      <td>黑龙江省</td>\n",
              "      <td>Helongjiang</td>\n",
              "      <td>绥化</td>\n",
              "      <td>Suihua</td>\n",
              "      <td>46</td>\n",
              "      <td>7</td>\n",
              "      <td>4</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2020-02-15 08:11:15.875</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>556</th>\n",
              "      <td>2020-02-15</td>\n",
              "      <td>黑龙江省</td>\n",
              "      <td>Helongjiang</td>\n",
              "      <td>鸡西</td>\n",
              "      <td>Jixi</td>\n",
              "      <td>45</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2020-02-15 08:11:15.875</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>564</th>\n",
              "      <td>2020-02-15</td>\n",
              "      <td>黑龙江省</td>\n",
              "      <td>Helongjiang</td>\n",
              "      <td>鹤岗</td>\n",
              "      <td>Hegang</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2020-02-15 08:11:15.875</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>561</th>\n",
              "      <td>2020-02-15</td>\n",
              "      <td>黑龙江省</td>\n",
              "      <td>Helongjiang</td>\n",
              "      <td>黑河</td>\n",
              "      <td>Heihe</td>\n",
              "      <td>13</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2020-02-15 08:11:15.875</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>558</th>\n",
              "      <td>2020-02-15</td>\n",
              "      <td>黑龙江省</td>\n",
              "      <td>Helongjiang</td>\n",
              "      <td>齐齐哈尔</td>\n",
              "      <td>Qiqihaer</td>\n",
              "      <td>36</td>\n",
              "      <td>8</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2020-02-15 08:11:15.875</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    update_date province_name  ... new_dead             update_time\n",
              "557  2020-02-15          黑龙江省  ...      0.0 2020-02-15 08:11:15.875\n",
              "556  2020-02-15          黑龙江省  ...      0.0 2020-02-15 08:11:15.875\n",
              "564  2020-02-15          黑龙江省  ...      0.0 2020-02-15 08:11:15.875\n",
              "561  2020-02-15          黑龙江省  ...      0.0 2020-02-15 08:11:15.875\n",
              "558  2020-02-15          黑龙江省  ...      0.0 2020-02-15 08:11:15.875\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cAjpm94qKqaJ",
        "colab_type": "text"
      },
      "source": [
        "### Q1. What is the number of confirmed cases in the past 7 days in the Hubei Province ?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a8pCGK_eKt5h",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "b48748ec-544e-4d9f-8fad-8f1ea1e6ffa1"
      },
      "source": [
        "x = daily_frm[daily_frm['province_name_en'] == 'Hubei'].groupby('update_date').agg('sum')[-7:]\n",
        "x"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cum_confirmed</th>\n",
              "      <th>cum_cured</th>\n",
              "      <th>cum_dead</th>\n",
              "      <th>new_confirmed</th>\n",
              "      <th>new_cured</th>\n",
              "      <th>new_dead</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>update_date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-02-09</th>\n",
              "      <td>27100</td>\n",
              "      <td>1480</td>\n",
              "      <td>780</td>\n",
              "      <td>2147.0</td>\n",
              "      <td>262.0</td>\n",
              "      <td>81.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-10</th>\n",
              "      <td>29631</td>\n",
              "      <td>1854</td>\n",
              "      <td>871</td>\n",
              "      <td>2531.0</td>\n",
              "      <td>374.0</td>\n",
              "      <td>91.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-11</th>\n",
              "      <td>31728</td>\n",
              "      <td>2310</td>\n",
              "      <td>974</td>\n",
              "      <td>2097.0</td>\n",
              "      <td>456.0</td>\n",
              "      <td>103.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-12</th>\n",
              "      <td>33366</td>\n",
              "      <td>2686</td>\n",
              "      <td>1068</td>\n",
              "      <td>1638.0</td>\n",
              "      <td>376.0</td>\n",
              "      <td>94.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-13</th>\n",
              "      <td>48206</td>\n",
              "      <td>3459</td>\n",
              "      <td>1310</td>\n",
              "      <td>14840.0</td>\n",
              "      <td>773.0</td>\n",
              "      <td>242.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-14</th>\n",
              "      <td>51986</td>\n",
              "      <td>3900</td>\n",
              "      <td>1318</td>\n",
              "      <td>3780.0</td>\n",
              "      <td>441.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-15</th>\n",
              "      <td>54406</td>\n",
              "      <td>4774</td>\n",
              "      <td>1457</td>\n",
              "      <td>2420.0</td>\n",
              "      <td>874.0</td>\n",
              "      <td>139.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             cum_confirmed  cum_cured  ...  new_cured  new_dead\n",
              "update_date                            ...                     \n",
              "2020-02-09           27100       1480  ...      262.0      81.0\n",
              "2020-02-10           29631       1854  ...      374.0      91.0\n",
              "2020-02-11           31728       2310  ...      456.0     103.0\n",
              "2020-02-12           33366       2686  ...      376.0      94.0\n",
              "2020-02-13           48206       3459  ...      773.0     242.0\n",
              "2020-02-14           51986       3900  ...      441.0       8.0\n",
              "2020-02-15           54406       4774  ...      874.0     139.0\n",
              "\n",
              "[7 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e-bjHabJLFoO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 531
        },
        "outputId": "9c54054a-2037-4246-9b99-28932ef13143"
      },
      "source": [
        "x.plot(y='cum_confirmed', figsize=(12, 8), marker='o', grid=True, \n",
        "       title='Hubei Province Confirmed Count in the Past 7 Days')"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fe5c9216940>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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JB6bwLiIiIlLPjsLDPJ6dy2sf5wFw+bgBfCdjKAN6dva5MhGFdxEREREAtuwr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\niIiIiPiEwruIiIiIiE/8f9nO8gz8R5BnAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lbZUnAxIKz-H",
        "colab_type": "text"
      },
      "source": [
        "### Q2. How do the daily new confirmed cases compare between the Guangdong Province and the Zhejiang Province?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2DeGGBZRLYkc",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 554
        },
        "outputId": "606e299d-5410-4625-8390-3dddc54b3611"
      },
      "source": [
        "frm1 = daily_frm[(daily_frm['province_name_en'] == 'Guangdong') | (daily_frm['province_name_en'] == 'Zhejiang')].copy()\n",
        "frm1['update_date'] = pd.to_datetime(frm1['update_date'])\n",
        "frm2 = frm1.groupby(['update_date', 'province_name_en']).agg('sum')\n",
        "ax = frm2['new_confirmed'][:, 'Guangdong'].plot(figsize=(12,8), label='Guangdong', grid=True, marker='*')\n",
        "frm2['new_confirmed'][:, 'Zhejiang'].plot(ax=ax, label='Zhejiang', grid=True, title='New Confirmed Comparison', marker='o')\n",
        "ax.legend(loc='upper right')"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7fe5c6a63b70>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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+lZjm9P2ttvRzQVEJt766ks5to/jL5EEBu/S1v+jevhX/95PBZP42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\nxGWRA5897AAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PRMWJuK3MlwR",
        "colab_type": "text"
      },
      "source": [
        "### Q3. What are the top 5 cities that have the highest death counts as of Feb 13, 2020?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tL-gbYhVMnmE",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 309
        },
        "outputId": "038e36ce-82e3-4194-a51e-0f706f1bf64e"
      },
      "source": [
        "daily_frm[(daily_frm['update_date'] == pd.to_datetime('2020-02-13'))].sort_values('cum_dead', ascending=False)[:5]"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>update_date</th>\n",
              "      <th>province_name</th>\n",
              "      <th>province_name_en</th>\n",
              "      <th>city_name</th>\n",
              "      <th>city_name_en</th>\n",
              "      <th>cum_confirmed</th>\n",
              "      <th>cum_cured</th>\n",
              "      <th>cum_dead</th>\n",
              "      <th>new_confirmed</th>\n",
              "      <th>new_cured</th>\n",
              "      <th>new_dead</th>\n",
              "      <th>update_time</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2474</th>\n",
              "      <td>2020-02-13</td>\n",
              "      <td>湖北省</td>\n",
              "      <td>Hubei</td>\n",
              "      <td>武汉</td>\n",
              "      <td>Wuhan</td>\n",
              "      <td>32994</td>\n",
              "      <td>1923</td>\n",
              "      <td>1036</td>\n",
              "      <td>13436.0</td>\n",
              "      <td>543.0</td>\n",
              "      <td>216.0</td>\n",
              "      <td>2020-02-13 22:12:44.102</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2476</th>\n",
              "      <td>2020-02-13</td>\n",
              "      <td>湖北省</td>\n",
              "      <td>Hubei</td>\n",
              "      <td>黄冈</td>\n",
              "      <td>Huanggang</td>\n",
              "      <td>2662</td>\n",
              "      <td>427</td>\n",
              "      <td>58</td>\n",
              "      <td>264.0</td>\n",
              "      <td>85.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2020-02-13 22:12:44.102</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2475</th>\n",
              "      <td>2020-02-13</td>\n",
              "      <td>湖北省</td>\n",
              "      <td>Hubei</td>\n",
              "      <td>孝感</td>\n",
              "      <td>Xiaogan</td>\n",
              "      <td>2874</td>\n",
              "      <td>209</td>\n",
              "      <td>49</td>\n",
              "      <td>123.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2020-02-13 22:12:44.102</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2480</th>\n",
              "      <td>2020-02-13</td>\n",
              "      <td>湖北省</td>\n",
              "      <td>Hubei</td>\n",
              "      <td>鄂州</td>\n",
              "      <td>Ezhou</td>\n",
              "      <td>1065</td>\n",
              "      <td>97</td>\n",
              "      <td>30</td>\n",
              "      <td>204.0</td>\n",
              "      <td>25.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2020-02-13 22:12:44.102</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2481</th>\n",
              "      <td>2020-02-13</td>\n",
              "      <td>湖北省</td>\n",
              "      <td>Hubei</td>\n",
              "      <td>荆门</td>\n",
              "      <td>Jingmen</td>\n",
              "      <td>927</td>\n",
              "      <td>93</td>\n",
              "      <td>24</td>\n",
              "      <td>231.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2020-02-13 22:12:44.102</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     update_date province_name  ... new_dead             update_time\n",
              "2474  2020-02-13           湖北省  ...    216.0 2020-02-13 22:12:44.102\n",
              "2476  2020-02-13           湖北省  ...      4.0 2020-02-13 22:12:44.102\n",
              "2475  2020-02-13           湖北省  ...      4.0 2020-02-13 22:12:44.102\n",
              "2480  2020-02-13           湖北省  ...      2.0 2020-02-13 22:12:44.102\n",
              "2481  2020-02-13           湖北省  ...      0.0 2020-02-13 22:12:44.102\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QNcxxwFNM5oR",
        "colab_type": "text"
      },
      "source": [
        "As you can see, this data set is very flexible, and can easily answer many questions that are otherwise difficult to be tackled."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bVhK9OZoNmVi",
        "colab_type": "text"
      },
      "source": [
        "## 3. Plotting Functions\n",
        "To expedite the analysis of the data, two convenient plotting functions are provided for visualization:\n",
        "* Time series plot: utils.tsplot_conf_dead_cured()\n",
        "* Cross-sectional plot: utils.cross_sectional_bar()\n",
        "\n",
        "For example, you can plot the total cumulative number of confirmed, dead, and cured cases in China by the following commands:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0a7idjFtjCY1",
        "colab_type": "code",
        "outputId": "9cb62dcc-dc5b-4bec-c47f-7334d18e370f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 555
        }
      },
      "source": [
        "fig = utils.tsplot_conf_dead_cured(daily_frm, title= 'Total Confirmed, Dead, and Cured Counts', figsize=(12, 8))\n",
        "plt.show()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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I63SkYy5wzUFePug6p44+6/JB17l80HXe+6xdu+c6q1evKbR8w4YNHH/88bvd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\n",
            "text/plain": [
              "<Figure size 864x576 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LSD5irEeOOTy",
        "colab_type": "text"
      },
      "source": [
        "Similarly, users can use the data from a specific city / province to obtain the same plot of that region. Also an optional parameter logy can be supplied to control the y-axis, so that it's easier for user to see if the numbers are growing exponentially. Following is an example of the same plot for the epidemic center Wuhan."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rRZQgzYWjtYt",
        "colab_type": "code",
        "outputId": "12e3b59d-eb18-4f38-8e0e-eab6d81a33fd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 555
        }
      },
      "source": [
        "fig = utils.tsplot_conf_dead_cured(daily_frm[daily_frm['city_name_en'] == 'Wuhan'], \n",
        "                                   logy=False, \n",
        "                                   title='Confirmed, Dead, and Cured Counts in Wuhan',\n",
        "                                   figsize=(12, 8))\n",
        "plt.show()"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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d+emnn1ixYkW586RkSvHM7JJ+eq9rBp3nmkHnufopLCx/Vu6SVq9eRWFhYUrb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UVdIOd1l8drafgMH/zTeTQ0RahXNycRkXFHQYeIyDhz3/MNx5Vn0BGNs9sPJnY3RdKWO9nd7AUa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\nCX3S2zEAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x576 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xTI_G1W5OmQw",
        "colab_type": "text"
      },
      "source": [
        "Cross-sectional plots are easy as well. Following is an example of comparing confirmed counts of all provinces:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ujEP1IFMOhg1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "outputId": "419a4ab3-303a-4a04-9d05-f8f6c43ed5c4"
      },
      "source": [
        "fig = utils.cross_sectional_bar(daily_frm, '2020-02-03', col='cum_confirmed', groupby='province_name_en', \n",
        "                                title='2020-02-03 Confirmed Count comparison among all provinces')\n",
        "plt.show()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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J8FPL7vc5DVGZC/nHc+45pGlBj/1lHfLULM/8c5ssdfDTyGu5ntdg339/dVIZAvtxyip/\nf6jH1gBOk7RlnfczrPpoj6XNo7v9TKMtE/xEDI7MAYqIiIiR6oXAC7uDH3hmVbtfU4acRUT8kwyB\ni4iIaCFJb6VMln8/cJHte1tcpRGlzoFaiTKv52nKsLs/2r5lkMvZlrLYwHcpy2z/05etRsTIkAAo\nIiKihVRWmOueF6PlWAkshlCdl7OIMixtbCuHdkbE8kkAtAJZa621PHXq1FZXI4bJY489xmqrrdbq\nasQwSXu3j7R1e0l7t5e098gxe/bsB2yv19u5LIKwAtlggw249tprW12NGCZdXV10dna2uhoxTNLe\n7SNt3V7S3u0l7T1ySOpzHmAWQYiIiIiIiLaRACgiIiIiItpGAqCIiIiIiGgbWQRhBTJ5ylSP2fuk\nVlcjhslh057mhDmZhtcu0t7tI23dXtLe7SXt3b95x85sdRWeIWm27e16O9cWPUCSxkoa19heuXFu\nZUlj6/aqS8jnAEnnSNpoaGscERERERFDoS0CIGA8sJ8kA3sA6zbObQycLelq4GVLyOc84PXAyku4\n7lkkTZJ0R3cQFhERERERrdEWfXi250u6tG6f3ePc7ZLmAI/avnwJ+Two6cFlqMLdwOvypWkRERER\nEa3VFgFQq7lMtLq91fWIiIiIiGh3CYAaJK0OfBLYznanpGnAwcCLbHc2Lp0paQzQCTwOHGT70TqX\n6O3AQ8B6wKbAUcBk4Gu2d+mlzFnALICJE9fj6GlPD9XtxQpmg/FlMmW0h7R3+0hbt5e0d3tJe/ev\nq6ur1VUYkLYLgCS9r5fD2wEP1CDmgrqP7TmSvgcc0+P6C23PA74i6TvAccBBwKGUZ/oAcA+wDTAJ\n6ABe21t9bJ8MnAxlFbisLNI+spJMe0l7t4+0dXtJe7eXtHf/5u3b2eoqDEjbtaDtr/c8JmlDSpCy\nLP4HOIsSAO0NHGD7lnruovr7Tkn3LmP+ERERERExSNplFbilsbRfjPQwZRgcwCrASwa3OhERERER\nMVgSAP2zvwLrN/a3Bcb2uGbtxvYM4Dt1+0LgaEnrAkiaLCkBUURERETECqIthsBJ2owyPA1JewEX\n2X607k+jzPl5nqRdgMuAKyVdA1wNXAOMkfR625fULE+TdCbQ/b0+X6i/P0/5XqEbJV0L/Bz4X0m7\nAxMlvQU433avs+fGjxvLrSvQN+jG0Orq6hoxY2Vj+aW920faur2kvdtL2nt0aIsACPgTJTj5LLAq\n8FTj3G3A7sBiSkCz0PaBPdKf2b1hu6OvQmwvAA5oHqurxV0IrF7zX7SsNxEREREREcunLQIg2080\ndhf0ONfcf3IIyl5MCa7g2YFXREREREQMs8wBioiIiIiItpEAKCIiIiIi2kYCoIiIiIiIaBsJgCIi\nIiIiom0kAIqIiIiIiLaRACgiIiIiItpGWyyDPVIsWLiIjiMubHU1lsq8fHFrRERERIwg6QGqJL1A\n0iWSLml1XSIiIiIiYmgMWw+QpDHAvsCmwB3AI8BY4FXAPbaPG6669Mb2HyR9GTi8lfWIiIiIiIih\nMywBkKQ1gB8DP7Z9TI9zPwJOGo56DMBjra5AREREREQMneEaAvcN4BHbX+p5wvYi4APDVI+IiIiI\niGhjsj20BUjrA/cA+9s+o5/rxgGHAofY7pC0KfBu4F22O+o1uwJbAFOBP9r+Qk13OHA30AFsC2wM\nvMn2fTXdy4EtgT8CLwS+ZtuSxgOfAG4DngT2BNa13VnTvQDYG/g/YHVgGnCc7QWSNgK+CJwB7Azs\nCFxm+8ONe/oAcCuwNnC37ct7ue9ZwCyAiRPXm370iacM8MmuGKZNWrPVVRix5s+fz4QJE1pdjRgm\nae/2kbZuL2nv9pL2HjlmzJgx2/Z2vZ0bjgDo5cCVwBts/7xxfFVgBrAVsB1wASUQObMR8HQAXTUg\nmgoca3vPGvTMtf0CSVsB5wCn2f5MTXc88BfbX5Ek4A/A5rafqgHHzsATwOPAhbZ/VNO9BfiA7U5J\nE4DfADva/ls9vy/wKtvvl/TvwGfr/u8krVzrv4XtRyTtDOxh+99q2suA64E7e+sJA5g8ZarH7L2i\njAYcmKwCt+y6urro7OxsdTVimKS920faur2kvdtL2nvkkNRnADQcQ+D+Vn93NA/afsL2T4GrKYHC\nacCd/eTzGHBwXUyhExhX87kRuKL+dJsLrFO31wNWs/1U3f8zZfGFd1EWZfhJI93fG9uvBh7qDn6q\ni4B3SRpj+7/r+d/VejwF3E7p7YHS4/RAI+19wBV9BT8RERERETH0hjwAsv17Ss/HeyWNXdLl/eRz\nD7AucCxw4wCKVk13P3CHpCn1+A7ApcAawMrd1/ViMfB0L8fG1p9+ywV+BmwDIGklytC7awdQ74iI\niIiIGCLDtQjCfpR5OV+vwUDTVGBB3f4bsEYd4gYwnRpsSFodOBv4JDC+HNJKtUdoSY4GPizpdcD1\ntk+y/SBwHfBvfaT5NbC2pLUbx2YC37G9cABl3gpcLekgYHdgH9t/GUC6iIiIiIgYIsOyDLbtmyRt\nARwGfFfSlcBdwHOArYFd63XzJZ0EXCvpGuA84O+S9gKuASYC76csSjCfsnz2tymLE+wj6a5a5GuB\nDeu8oZUovUZ72P5Tj6q9HTi9zlO6HNgQ2FTSDNuXSdoT+ICka4HVKMP4/r0GaPsAEyW9mxKYvQqY\nAuwt6SuUQO1JytykxwfynMaPG8utmVMTERERETFkhu2LUG0/ABzZy6nTe1z3KeBTjUMXNLY3bGy/\nBEo3kO3pdbEDXFZ1eFczT0lfB26QdAdlGNudwEfr8LxXNq4bC3y65tE9fO+Y3u5H0ndsn1nLN/Bz\nYHLj/GeBs4BbJN1LGRp3KfDxuvR3REREREQMs+EaAjdkGsGKu7ebJHVSFkSYaHtb4KXAl4HP9ZLX\not7yWFK5fVzyMeAztifb3p6yTPZzKMPoIiIiIiKiBUZ8ADQAB1GW0l4EzwQsNwJXDVWBdb7S7rav\n6T5mewFlEYSbhqrciIiIiIjo37ANgWuhw4H3SZpMmTe0GFiF0gs0JGw/KulTkj5KCXgWUhZzmGP7\nj0NVbkRERERE9G/UB0B14YPe5h4Ndbk/GO4yIyIiIiKif+0wBC4iIiIiIgJIABQREREREW0kAVBE\nRERERLSNBEAREREREdE2Rv0iCCPJgoWL6DjiwlZXY6nMOzZfaxQRERERI8eI6gGS9O+SJvRzfhNJ\nl0nqGL5aRURERETESDHSeoDeAawk6YHGsVWBE4GvABcDL1raTCWtC9wATLG9UNKJwB22TxqEOkdE\nRERExApixARAkjYBDrE9u8fxbwHXAkfZflrSrUubt+2/SdrN9sJ66PPA48td6YiIiIiIWKGMmADI\n9h3AHc1jkt4LvAHY1vbTy5n/DY3t+5cnr4iIiIiIWDHJdqvrsEwkvRS4FHij7Ssbx7uAT1ECo+mU\nnpw9uwMkSXsCTwGr1/Mfr9vH13R3AvsAk2wfX9McAqwCvBr4qu2LJa0NfBM4AXgL8ArgTtt7N+qy\nP/AQIGCx7fN6uY9ZwCyAiRPXm370iacMwtMZPtMmrdnqKoxY8+fPZ8KEPqe0xSiT9m4faev2kvZu\nL2nvkWPGjBmzbW/X27kR0wPUVOfs/AD4eDP4adjK9pH12rOAnYCfSnoLsANwCfA34EnKnKHVKQHT\np4AJwG7ALTX9O4FVbH9R0o3A3pS5RjOAXYEv2/6IJAFXS5pme46kzYG3235jzedMSW8AHrb98e6K\n2j4ZOBlg8pSpPmHOyGqSeft2troKI1ZXVxednZ2trkYMk7R3+0hbt5e0d3tJe48OI+vdNiBpDPBd\n4ArbX+njsnMb27cC69ftvYHTbV9U97t/I+kPALYfknQR0FFPzQbuqKvPbQ+Mq9edI+lu21fUfUu6\nGVinptsCeLBRjzuB+2x/eSlvOSIiIiIiBsmIWga7+jTwXOqwsW6S1pO0Tu9JUP29CvCSpSnM9s3A\nzsB7KYstLEl3WVcAUyV1B5nTgV8uTdkRERERETG4RlQAJGlX4CDgrbZ7rtK2N7DGErK4EPhQ9/cE\nSVpH0suWUOYOwHtsnwBsWA5plQFU96/A6cDHJO0GHNlzBbuIiIiIiBheI2YIXF0G+wzg50CnpE5K\nALcq8ELgQGAB8DzgPZJOpdzfK4FNJF0MfIsy5+fXkn4L/Ao4rkc5LwZeD6whaVNgY2AzSQdQ5g29\npuZ/N7CupIOBs4DNgC2B3epcoX2ArYHDbD88kHscP24stx47c1keT0REREREDMCICYDqMthr93PJ\nv0saa/t/64IEsr2YsgBC0+H1p9digD8C+1GGsq1k+4+UBRe6/RjKXCTbq0uSy1J6VwHbdl8k6ZuU\nYW+3SLqz5jcb+LDtxwZ21xERERERMZhG1BC4JbG9qP52DX6WxsrA/baf6k5v+6l+ylrcXVYflxwE\n/Mj2c22/FHg5cDvwr0tZr4iIiIiIGCQjpgdoKEkaD9xoe8EgZnsIZbgdALYXSroOeGIQy4iIiIiI\niKWQAKh4HXDkIOd5IPCJGvR09yTNt/3rQS4nIiIiIiIGKAEQYPuCIcizC+ga7HwjIiIiImLZjao5\nQBEREREREf1JABQREREREW0jAVBERERERLSNzAFagSxYuIiOIy5sdTX6NS9f1BoRERERI9io7QGS\nNFbSuMb2yo1zK0saW7dXbVUdIyIiIiJieI3aAAgYD+wnycAewLqNcxsDZ0u6GnhZKyoXERERERHD\nb9QOgbM9X9KldfvsHudulzQHeNT25S2pYEREREREDLvR3AMUERERERHxLLLd6joMGUkdwB221cu5\nY4AO2/vX+UBvBx4C1gM2BY4C1gK+CZwAvAV4BXCn7b1rHhsABwNPAjsCb7X9mKTtgXcAN1GG2O0I\nHGX7+73UYxYwC2DixPWmH33iKYN1+0Ni2qQ1W12FUWP+/PlMmDCh1dWIYZL2bh9p6/aS9m4vae+R\nY8aMGbNtb9fbuVE7BK5J0vt6Obwd8EDdPpTyLB4A7gG2ASYB2wO7Al+2/RFJAq6WNM32HOB0YH/b\n90raHNha0uya32bAp22fUs+dAfxTAGT7ZOBkgMlTpvqEOSt2k8zbt7PVVRg1urq66OzsbHU1Ypik\nvdtH2rq9pL3bS9p7dFix320PEttf73lM0oZAR93dGzjA9i11/6L6+05Jd9u+ouZjSTcD69TzR9bg\nZzNKwDTO9hOSTqUERg/WdHMldaeJiIiIiIgWyRygYhXgJUtxffeQurl1KN3GwLwBpomIiIiIiBZJ\nAFRcCBwtaV0ASZMlDSQg+hIwF7gUmFySapWhq2ZERERERCyPUTsErg5L616sYC/gItuP1v1plDlA\nz5O0C/B5Si/OjZKuBX5u+6uS3gysK+lg4CzKvJ4tgd0k3QhsSPmOIQNXAp8DjgRmAtNr3pcDbwXW\nk7SL7Z/0Vefx48Zy67EzB/tRRERERERENWoDIOBPlMDms8CqwFONc7cBuwOLgXHAQtsH9JLH+bZX\nlySX5fKuArZtnN+jsf3/oHQBAb+0fXgj3Rn1JyIiIiIiWmjUBkC2n2jsLuhxrrn/ZD95LK6/B7xW\nePPapUkXERERERFDL3OAIiIiIiKibSQAioiIiIiItpEAKCIiIiIi2kYCoIiIiIiIaBsJgCIiIiIi\nom0kAIqIiIiIiLaRACgiIiIiItrGqP0eoJFowcJFdBxxYUvrMO/YmS0tPyIiIiJiKI3KHiBJYyWN\na2yv3Di3sqSxdXvVVtUxIiIiIiKG36gMgIDxwH6SDOwBrNs4tzFwtqSrgZe1onIREREREdEao3II\nnO35ki6t22f3OHe7pDnAo7Yvb0kFIyIiIiKiJUZrD1BERERERMQ/ke1W12FISOoA7rCtXs4dA3QA\nhwCfBLaz3SlpGnAw8KK6vxpwPHAR8HJge0qv2c62n5A0ATgMWAC8EdjP9t2SXgh8FPg50AnsCHzT\n9pd6qcssYBbAxInrTT/6xFMG6xEsk2mT1mxp+e1k/vz5TJgwodXViGGS9m4faev2kvZuL2nvkWPG\njBmzbW/X27lROQSuSdL7ejm8HfCA7UclXVD3sT1H0veAYxrXvQ242vbHa35nAzsB5wMnAl+3fa2k\nNYEZwHcoAc3rgE/b/r6kdYHfAv8UANk+GTgZYPKUqT5hTmubZN6+nS0tv510dXXR2dnZ6mrEMEl7\nt4+0dXtJe7eXtPfoMOoDIPLRrHoAACAASURBVNtf73lM0oaUHqAlpb28zhe6onF4LrBO3f6q7esl\nbQy8EPhDPf7flF6lP9d8/iZp4bLfRUREREREDIZRHwANwLKMAeweVneDpMOBO4CbBq9KEREREREx\nFBIAwV+B9Rv72wJjB5j2I5R5VD+QNBP4k6RVlrUi48eN5dZ8EWlERERExJAZlavASdoM2K9u7yVp\n9ca5aZS5PdtI2oXSe3OlpGsk/RdwPzBG0uslzaAMlXuPpEmStgJ2AF4vaSNgI+ANkt4G3AB8CHgD\nsCcwVdLeksZJ2h2YKGk/Sf+0KENERERERAyP0doD9Cfg88BngVWBpxrnbgN2BxYD44CFtg/skf5M\nAEmy3dEdtNi+C9i5cd2HeqQ7qaa7wPYXa3oD5wJZMiQiIiIiosVGZQBk+4nG7oIe55r7Ty4hHzd/\nL0X5y5QuIiIiIiKG1qgcAhcREREREdGbBEAREREREdE2EgBFRERERETbSAAUERERERFtIwFQRERE\nRES0jQRAERERERHRNkblMtgj1YKFi+g44sIhL2fesTOHvIyIiIiIiBVRW/YASXqNpC8tZZotJf12\nqOoUERERERFDry0DIOB1wDskjV2KNJsCL1iWwiSNkzRP0kbLkj4iIiIiIgZH2wVAksYD84C/Am8c\naDrbPwLuW5YybS8EXmv77mVJHxERERERg6PtAiDgX4CLgTOB/YarUNu3D1dZERERERHRO9ludR2G\nlaRP2P6cpI2BW4CNbD8iaQzwbmBtYBVga2AasKftuTXtPGB3YF/g5cAc2++XtDrwSWA7252SpgEH\nAy+q++sDxwPH2J7Xoz6zgFkAEyeuN/3oE08Z4icA0yatOeRlxJLNnz+fCRMmtLoaMUzS3u0jbd1e\n0t7tJe09csyYMWO27e16O9dWq8BJ2gCYJGn3euh2YC/gm8DzgYOA64CDbC+SdBDwr8BhjWw6bB9e\n87tK0ott3yzpAmA7ANtzJH0POKam2QjYubH/DNsnAycDTJ4y1SfMGfommbdv55CXEUvW1dVFZ2dn\nq6sRwyTt3T7S1u0l7d1e0t6jQ1sFQMA+lF6Y+wEkrQu8C/im7TskXQjMs72oXj8XeGkzA9vnNnZv\nBdYHbu6vUNs3SLplkO4hIiIiIiKWUbvNAZrcHfxUPwS2l/T8ftJoCXl2n2+vsYQRERERESNQ2wRA\ndV7Orc1jth8CfsLgLIbwV0pvULdtgaVZZjsiIiIiIobYqB8CV7/r59XAR4AfS9rU9h/ruZcBTwEH\nS1pEWdhgC0k3AA8AuwJbS9oK6ADWknQwcDbwXGArYBdJN9qeK+lKSdcAVwPXAGMkvYHSS7QpMFPS\nt2w/3ltdx48by63HzhyiJxEREREREaM+AKqLGVxhu0uSaAxps/0b4O0A9dyxti1JLsvjfaT7Wkm/\ns71WXS0O238FtulR1oE9ij+zpl0ZmEx53osH/SYjIiIiImJARn0ABCUIqr9NH3N13FgPvLndSx5L\nHcDYfqpuLlzatBERERERMXjaZg5QREREREREAqCIiIiIiGgbCYAiIiIiIqJtJACKiIiIiIi2kQAo\nIiIiIiLaRgKgiIiIiIhoGwmAIiIiIiKibYza7wGSNLb7u3skrWT76VbXaUkWLFxExxEXDmkZ846d\nOaT5R0RERESsyEZzD9Amkj4g6WngTZLGSZonaaPhroik7SVdM9zlRkRERETEs43aAMj2bcB5wBO2\nz7e9EHit7btbUJ3rgD1bUG5ERERERDSM2iFwvbF9e4vKfRr4cyvKjoiIiIiIf5DtVtdhyEjqAH5n\ne4Kk9YHjgWNsz5O0AXAw8CSwI/BW249J2h54B3AT8LJ67ijb3695TgA+AFwJbA6cC9wNvBPYFLgB\nuB7YC7gP+BEwGfiU7b16qeMsYBbAxInrTT/6xFOG4En8w7RJaw5p/jFw8+fPZ8KECa2uRgyTtHf7\nSFu3l7R3e0l7jxwzZsyYbXu73s61Uw/QRsDOwDF1/3Rgf9v3Stoc2FrSbOBQYDPg07ZPqefOAL5f\n0/0HMMf2ZZL+jzK87SLgQmB/4EHgfGAB8B3biyVtCby0t0rZPhk4GWDylKk+Yc7QNsm8fTuHNP8Y\nuK6uLjo7O1tdjRgmae/2kbZuL2nv9pL2Hh1G7RygnmzfANzSOHRkDX42AyYB42w/AZwK3GT7wZpu\nLrBOI92WwAP13HxgDUqv0s+AtwLvoQRZp9peXK/73lDeW0REREREDEzbBEC9mCvpGGBjYN4SrlVj\n+3xgBwBJU4A7G8HSw8DnKYHQhoNc34iIiIiIWE7tEAD1NcnpS8Bc4FLKHB1JWmUA+f0QeJ6kN1MC\nodd1n5C0KXAv8F7gbEnPWZ6KR0RERETE4Brtc4AEPCJpDLATZZGCmZK+Remh2YMSIF0JfA44EpgJ\nTJe0C3A5pTdnPUm72P4JZWntTwMXd3/RKoCkPSiLI3wYuAt4GvihpPdRFlJYW9LrbV/SV2XHjxvL\nrfmi0oiIiIiIITPaA6CVKEPUFku6jNLTsxKw2PYejev+H5QuIOCXtg+XJJcl8s6oP932Ay6o1z9C\nCXS+TukZOhcYBywCXl2vHwucBZwJrDwkdxkREREREQMy2gOgNajBiu2n6rGFfV3sxprgze1udQns\nDwKdtu+tx9YHzgHOqz1Ci3okW9zYfnIZ7iEiIiIiIgbJqJsDJGmspPXq7nTKqm6DZUdgTHfwA2D7\nfuAS4NFBLCciIiIiIobAaOwB2hL4maT/Ai61fc8g5n0RME3Sgfxjns94GkteR0RERETEimvUBUC2\nrwfWH6K8FwPHDUXeEREREREx9EbdELiIiIiIiIi+JACKiIiIiIi2kQAoIiIiIiLaRgKgiIiIiIho\nG6NuEYSRbMHCRXQcceGg5Tfv2JmDlldERERExGiwQvYASRojaXdJ57S6LhERERERMXq0tAdI0rrA\nYcD9wF+ANYBO4BfAZGCdllWuF5K2B/7b9vatrktERERERCy9lgVAkjqAS4D9bF/VOH4mcCTwbeD1\nLalc364D9mx1JSIiIiIiYtm0cgjcmcC5zeAHwPZC259uUZ36Zftp239udT0iIiIiImLZyPbwFypt\nBdwAvNr2r/q4pgM4DTgR2Al4FfBl26fV82sAhwLXA67nv2b7L5JWA44HLgJeDmxP6e3a2fYTNf1u\nlCF3DwLr2z69Ht8IOBi4Flitpp1v++OSNgc+ZXsvSWOAdwNrA6sAWwPTgD1tz615bQbsAtxYz33N\n9lM97nMWMAtg4sT1ph994ilL/0D7MG3SmoOWVwy++fPnM2HChFZXI4ZJ2rt9pK3bS9q7vaS9R44Z\nM2bMtr1db+daNQTuRfX3fUu4bhPgdtsHS1qbEuycVs99CzjZ9s8AJM0FzpW0A7Ad8Dbgatsfr+fP\npgRS50taB/is7a3quc9L+hbwNCVQeYft2+u5DYEtaplbAi+t288HDqIMizvI9iJJBwH/SpnXBHA6\nsIftuyStBFwk6U7go7bvBbB9MnAywOQpU33CnMFrknn7dg5aXjH4urq66OzsbHU1YpikvdtH2rq9\npL3bS9p7dGjVELiH6u/nLuG6O2z/FsD237sP1h6eNwOXdR+zPQ9YGdjW9uXAHOCKRl5z+ceiClOB\nxxvn/gw8AnwJ2KA7+Kmub5Txvcb2HcCFwFW2F/VSBpSA6YFGGevafld38BMREREREcOrVQHQFZTA\n4GW9nZS0yhLSG1gELO5xfDElCOqL6u/fAs+pw+gAdgAurXluIGl8I80ilo4a2+fXvJtlRERERERE\ni7QkALL9OPAe4AOSNmieq3NrPjaA9D8GXtNIN4USGF0zgCo8CXwB+A9JbwDOsH2e7d/X9F9oXDtx\nAPn15ThgP0k7UXqcPrIceUVERERExHJq2TLYts+XdAdwmKQ/UIbFrU6Zp3MzsDuwqaS3AT+kLIk9\nUdLbge9R5tp8WNKawFOUxQ52s/2kpBlAB/AeSd+gBDE7AFMlXUwZmrYfcIDt+3tUbS/ga5IuAbqA\nNQFqOf8CrC3p9cBdNc8tJN1A6dHaFdi6LvJwO3B2rdPNA3km48eN5dZjZw74GUZERERExNJp6Reh\n2v4d8NEeh/9Xkigr1J0oaWydY/NToLnsxiPAMY39CxrbXbY7aj7YvgvYufukpHsowcvNkm6nDFv7\nPfAh2/fR+K4fSZ3A/sBjwFmU5btXpgRdb7JtSXJZTu9ZPTySDgWukHQXsBD4G3C07d8M8BFFRERE\nRMQgamkA1JcaTLhuL+0cnO70z/zuxd7An22vCyBpbD32MeDDfeT5dGP3yd7Ka5K0BfBKYOPG0ttb\nASew4n3Ba0REREREW1ghA6BhcBhluBpQgixJ1wFjB7GMdwHXdgc/1c2UYXUREREREdEC7RoAHQgc\nKmk2/1gOe7HtM5sX1R6bQylzh7bsXpJ7gI6lzG8aC/ydskLdasB/LnftIyIiIiJimbRlAFQDmSUG\nM7ZvBN7aPSdpKct4EPjEstUwIiIiIiKGQlsGQEurOScpIiIiIiJGrlZ9EWpERERERMSwSwAUERER\nERFtI0PgViALFi6i44gLlyuPefki1YiIiIiIPo26HqC66lr3dgK8iIiIiIh4xqgLgIBNJH1A0tPA\nmySNkzRP0katrlhERERERLTWqAuAbN8GnAc8Yft82wuB19q+u8VVi4iIiIiIFht1AVBvbN/e6jpE\nRERERETrqXzFzegiqQP4ne0JktYHjgeOsT1P0gbAwcCTwI7AW20/Jml74B3ATcDL6rmjbH+/5jkB\n+ABwJbA5cK7tu+rxo4DZwNuBjwILgW8AV9k+RtLrgKOBy2wf06Ous4BZABMnrjf96BNPWa57nzZp\nzeVKH8Nn/vz5TJgwodXViGGS9m4faev2kvZuL2nvkWPGjBmzbW/X27l2WCRgI2Bn4Ji6fzqwv+17\nJW0ObC1pNnAosBnwadun1HNnAN+v6f4DmGP7Mkn/B1wn6SLgV8Dats+WdHnd/oOkq7orYPsXkl7d\nW+VsnwycDDB5ylSfMGf5mmTevp3LlT6GT1dXF52dna2uRgyTtHf7SFu3l7R3e0l7jw6jfgic7RuA\nWxqHjqzBz2bAJGCc7SeAU4GbbD9Y080F1mmk2xJ4oJ6bD6xBCaouA14p6XzghbabZUVERERExApk\n1AdAvZgr6RhgY2DeEq5VY/t8YAcASVOAO2uw9ACwFXAmcKqkfer1o29sYURERETECDeaA6C+ApAv\nAXOBS4HJgCStMoD8fgg8T9KbKYHQ6+rxNwPPq3OF9qXMHwL4K7A+pYBVgJcAY4mIiIiIiJYZrXOA\nBDwiaQywE7ApMFPSt4ANgT0oAdKVwOeAI4GZwHRJuwCXA28F1pO0i+2fUJbW/jRwse1FjbJ+D5wk\n6bvA2pQAC+C7wAWSLqn5/Q7YXNKLbd/cW6XHjxvLrcfOHLSHEBERERERzzZaA6CVKEPUFku6jNLT\nsxKw2PYejev+H5QuIOCXtg+XJJel8c6oP932Ay6o1z8CPA183fa3gX/pWQHbDwGvGvxbi4iIiIiI\nZTVaA6A1qMGK7afqsYV9XezGWuDN7W51qesPAp22763H1gfOkXSe7YcHse4RERERETFERs0cIElj\nJa1Xd6dTVnUbLDsCY7qDHwDb9wOXAI8OYjkRERERETGERlMP0JbAzyT9F3Cp7XsGMe+LgGmSDgTu\nogx/Gw+canvxIJYTERERERFDaNQEQLavp666NgR5LwaOG4q8IyIiIiJi+IyaIXARERERERFLkgAo\nIiIiIiLaRgKgiIiIiIhoGwmAIiIiIiKibYyaRRBGgwULF9FxxIXLnH7esTMHsTYREREREaPPiOgB\nkrSWpJMkvXsIy9hA0g8k3TpUZURERERERGutcD1Akl4LbAM8BGxG+aLRs4GtgOuHqlzb90n6JLDs\nXTAREREREbFCW6ECIEkTgQ/Z3q1x7LO2b5XUNQxVeGwYyoiIiIiIiBZZ0YbATQKmSXpu41i+gDQi\nIiIiIgaFbLe6Ds+QJOBc4NWUwOcrth+v544B7gfWALYFNgH2tP2nen4/YENgOvAT29+WtBpwPHAR\n8HJge0qv1862n5A0Fvgo8CDwd2AnYCfbHTXPDYFZwG+AlWseX7T9oKS1gW8CJwBvAV4B3Gl778b9\n7E8Zyidgse3zernnWbUMJk5cb/rRJ56yzM9v2qQ1lzltDL/58+czYcKEVlcjhknau32krdtL2ru9\npL1HjhkzZsy2vV1v51aoAAhA0hjgEOAo4Cngw7a/VwOgzYADavDyXmCK7Y9J2pESDB0q6QXA/9je\nSdJrgHOAD9o+o+Z/NnCG7fMlHQE8afvL9dw2wI9sd9R6XAXsb/vmev6VwH/YfpOktwLfA15n+4oa\nvF0NHGh7jqTNgS/bfmNNeybwMPCw7Y/3du+Tp0z1mL1PWuZnl1XgRpauri46OztbXY0YJmnv9pG2\nbi9p7/aS9h45JPUZAK1oQ+Cwvdj2ScAU4HTgDEkz6umf2X6ibt8KrF+37wSOkrQy8CpgXM3rcmAO\ncEWjiLnAOnV7FnBB49zfG9ubARt3Bz81v18Dr5S0ge1zgLttX1HPGbi5kfcWlJ6lbncCt/UV/ERE\nRERExNBboQIgSS+VtDqA7UdsHwn8J2VVuF6T1GtvB6YBnwCuHUhR9ffExnZPi4GnezluynC4JeV9\nBTBVUvdCE9OBXw6gbhERERERMURWqFXgKL0uOwOfaRwbRwkcdu0rkaRNgC9S5uG8uhzSKrafXEJ5\nPwPeCxzWy7k/AHdLeqHt39dyXgVca/svA7iXv1J6sD4m6bfAkbZn95dg/Lix3JphbBERERERQ2ZF\nC4CuB/aS9D/AdcAqwK+Ax4HtgC0k/Y4SnPxL3d8KeA6wESWYuRWYDBwp6XKgA3iPpG9Qenx2oPTM\nXAwcDJwu6XxKMLQYWFfSW2z/qM7zeb+kaym9ZdOBvQAkvbleezBwFiV42xLYTdKNwD7A1sBhth8e\nsicWEREREREDtkIFQLZvAt7c83hdrW0325Y01vYi4MM9Lpvc2N6kplNd0KB7qNxdlB6mpjc1yhkD\nfKPmj+17gKMb157b2D7f9uq1DFMWTNi2kdc3KQHTLZLupAyNm01Z1CHfNxQRERER0QIr1Bygvthe\nVIMMuoOTAabrTuPu7SVcv3ig+dte3CyjFwdRVpR7ru2XUpbQvh341wFVPiIiIiIiBt0K1QM0yhwC\nvKh7x/ZCSdcBT/SdJCIiIiIihlICoKFzIPCJGvQ8VY/Nr0tpR0RERERECyQAGiK2u4CuFlcjIiIi\nIiIaRsQcoIiIiIiIiMGQACgiIiIiItpGAqCIiIiIiGgbmQO0AlmwcBEdR1y4zOnnHTtzEGsTERER\nETH6tHUPkKRNJF0mqaPVdYmIiIiIiKE34nuAJL0W2AZ4CNgMeNT2ZySdA5xh+0f9JO+g8V09ERER\nERExuo3oAEjSROBDtndrHPts3TwUuL+/9LYvk3TrEFYxIiIiIiJWICN9CNwkYJqk5zaOHQdg+07b\nT/WeLCIiIiIi2pFst7oOy0ySgHOBV1MCn6/YflzSqsD7gL/ZPqNedyQwDphcr9/D9hxJXcCngDcA\n04HHgT0BUXqRDrHdIWlT4N3Au2x31PJ3BbYApgJ/tP0FSeOAw4G7KUPstgU2Bt5k+75e7mEWMAtg\n4sT1ph994inL/DymTVpzmdPG8Js/fz4TJkxodTVimKS920faur2kvdtL2nvkmDFjxmzb2/V2bkQH\nQACSxgCHAEcBTwEfBi4Hvgucbvs0Se8FdrS9b03zCuAW2w/WAOhc2yfWc2cB37b907o4Qlcj4Hlm\nX9JU4Fjbe9agZ67tF0jaCjgHOM32Z2q644G/2P5Kf/cyecpUj9n7pGV+FlkFbmTp6uqis7Oz1dWI\nYZL2bh9p6/aS9m4vae+RQ1KfAdBIHwKH7cW2TwKmAKcDZ1AWNri8cdkbgYsbaa60/WDj/LmN7VuB\n9QdQ9GPAwTUA66T0LmH7RuCK+tNtLrDOAG8pIiIiIiKGyIgOgCS9VNLqALYfsX0k8J+UVeGangLW\nWpqs6+8+u8ds3wOsCxwL3LgUeUZERERERIuM6ACIsuz1B3scGwf8ssexHwLvk7QW/H/27jW8rqpc\n+/j/ppRSDKCQstkWa4AqbKGwpRVBURNERKAqAkVF5KAWlS0CgoBbK7wvWxBBwDMgCoJu5FU5y8FT\nEA+IFIQKCAhU5KCcD8FCS3u/H+YILkPSZrVZWUnW/buuXGvOOeYY41lrfMlzjTHHBEmrSdpkEO0/\nAqxRlrhB9YzQuNLG6sB5wGeBidUlrVxmhCIiIiIiYgQa1dtgAzcAu0v6GnA9MAH4FdXMzeuAyZKu\ntP3/JG0A/ELSncBfgP9T3iH0MmA/Sd+k+j1eD6xf6t0v6RTgOknXAhcCj0naHbgWaAc+Avwe6AFO\nAb4DTAP2kHRfiXNbYF1JU23/eaAvM3H8OG7LczwREREREQ0zqhMg2zcD7+h7XdIEqud+Vip/2P48\nZYvsmvuusr1h2SVOtpcAb+nTx9FUu8T1uqTmeN2a401Km7I9vbSJq10m3r983zAiIiIiIobSqE6A\nBmL72XK4uPwNdN/i8mmW8rxPnX279jMiIiIiIkaOPK8SEREREREtIwlQRERERES0jCRAERERERHR\nMpIARUREREREy0gCFBERERERLSMJUEREREREtIwkQBERERER0TLG5HuARqsFixbTccSlddebf9xO\nDYgmIiIiImLsGXMzQJLeJukESZa0v6TtJO0p6VuSNllG3XdJ+mE5lqS7JL2snB8s6aTh+A4RERER\nEdEYY24GyPZlkm4FPgFcYXs+gKR1gDOArZZS/TLgt6UdS9oFuLeUfYsx+HtFRERERLSSlviHXtI4\noBM4f2n32V4ALKg5v7Hm+IlGxRcREREREcNDtpsdw5CT1AHcDRwCPAbsAbQBH7L9J0ntwEzgYWAj\n4O+2z5a0VbnnA5LWAI4ELgd+CbwV2M72oZJeBBxfyrYGtqRKJnew/UyJYSawBvAosI7tswaIdTYw\nG6C9fdL0OSefXvf3nTZ5zbrrRPP19PTQ1tbW7DBimGS8W0fGurVkvFtLxnv06Orqmmt7Rn9lY30G\n6PyyBO5MSfsB15TngL4IfA9YBNwOvE3SOcCbgA1L3fWBnYErgAnADsCLS9kM4N3ANbY/BSDpPOAt\nwMWS1gKOsb15KfucpG8DC23vXxug7dOA0wCmbDDVJ86rf0jm79lZd51ovu7ubjo7O5sdRgyTjHfr\nyFi3lox3a8l4jw1jbhOEgdj+FtVszLuAN9i+0Pblti+y/RFXU2Hfr7n/RmBuOX4GuKCm7CpgHnB1\nTRe3AGuV46nAP2rK7gGe7Jv8RERERETE8GqZBKh4ChCwblkGN9RUPm8CVivL6KDaeOHnDegvIiIi\nIiLqMNYToNV6D8rzPS8GzgZ+DZxYNkdA0hskDeWCzmeBY4FPS9oeONv2hUPYfkRERERELIcx9wyQ\npM2AD5bTb0s6GxhHtSztDbYfk7QXcCZwu6RryvGLgFnAFEmvtf27mjY7qDZN2FjSpsAkoAPYT9Kp\nQDvVLM9USVcCmwF7AfvafnCwsU8cP47b8lLTiIiIiIiGGXQCJOldwOeBdaiWeonqdTlrLLXiMLN9\nE3Bg+RvonvlU22I/T9J44ETgC8AqtbcD9wOHlePxwM22OySptHcf1SYJvW09QJUQ3SrpLqrf6nbg\nYNt/X7FvGBERERERy6ueGaDjgZm2b21UMM1ke1HN6bPlczXgftsLa8oW1tQZaA/xWcA9tteG599D\nNAs4nGpr7oiIiIiIaIJ6EqC/j9Xkpz9ldudp23csR/VPUG2hDYDtxZKup1qKFxERERERTVJPAnSd\npO9TbQfdO0OC7R8NeVQjwxuBzy5n3Q8CB0qayz+3w15i+5whiSwiIiIiIpZLPQnQGlT/zG9fc83A\nmEyAyrt+lrfuTVRbYUdERERExAgy6ATI9r6NDCQiIiIiIqLRBv0eIEmvlPQzSX8s55tJ+nTjQouI\niIiIiBha9bwI9XTgSGARPL/M692NCCoiIiIiIqIR6kmAVrN9bZ9rzw1lMBEREREREY1UzyYID0va\nkGrjAyTtBjzQkKha1IJFi+k44tK66sw/bqcGRRMRERERMfbUkwAdAJwGbCzpPuBuYM+GRDVIkl4M\nHA1cb/usYehvNeDjwMq2/2+j+4uIiIiIiKFVzy5wdwHbSXoRsJLtp2rLJe3dyCRE0rbAq4HHgY2A\np4DzgM2BGxrVbx9rA1sAN9dbUdLvgY/a/v2QRxUREREREYNSzwwQALafHqDo40BDEiBJ7cDBtmfW\nXDvG9m2SuhvRZ39s/1XSpUDHclTfHbhnaCOKiIiIiIh61LMJwrJoCNvqazIwTdK/11z7fAP7G3K2\n59te0uw4IiIiIiJamWwPTUPS9ba3GJLGXti2gAuAN1AlPl+2/Y9SdhTwILAG1fK09YHdbP+llO8F\nrAtMB35s+ztlGd/xwOXA1sCWVLNhO9h+ptSbWdp8FFind3mfpH2ADYGHgNcA04D9bF9fyncGNgWm\nAnfaPlbSGlRbiF9u+6o+3202MBugvX3S9Dknn17XbzNt8pp13R8jR09PD21tbc0OI4ZJxrt1ZKxb\nS8a7tWS8R4+urq65tmf0VzaUCdANtl89JI313/5KwMeAzwALgUNsn1sSoI2AfW0/I2l/YAPbh0t6\nI1UydKCkVwBfs/0WSW8CfgQcZPvs0v55wNm2L5a0FvAL25uXss8B/176/S3w/tLuo5LeSpUA7SFp\nKnCc7d0kjQdusf2KsnvehcB/2e4e6DtO2WCqV5p1Sl2/S3aBG726u7vp7OxsdhgxTDLerSNj3Voy\n3q0l4z16SBowARrKJXC/HsK2XsD2EtunABtQPWt0tqSuUnxF78wNcBuwTjm+F/iMpFWAbYDxpa2r\ngHnA1TVd3AKsVY6nXgAn7AAAIABJREFUAv+oKbsHeNL2/uX8l7Yf7ae/p4EDSrLWWdPfncB1y/nV\nIyIiIiJiiAw6AZL0b5LOkHRZOX+VpA/0ltv+r0YEWPp6jaTVSz9P2j4S+ALVrnD9Vin33kW1RO2/\nGVwC0vsc003AamXpGsBWwM+XVc/2A1Q7xR0H3DiI/iIiIiIiYhjVMwN0JnAF8NJyfjtw0FAHNICN\n+ulrPPDLpVWStD5wAtW7gtaqLmnCIPp7FjgW+LSk7amWxl24rEolSTsP+CwwsfS3cpkRioiIiIiI\nJqtnG+x22+dJOhLA9nOSFjcorr5uAHaX9DXgemAC8CuqZWozgE0l/RG4A3h7Od8cWI0qYdufaqna\nFOBISVdRbWW9n6RTgXaqWZ6pkq4ENgP2onqu6MHeICR1AG8E1i/L734DzAJeLun1VEvu2oGPAL8H\neoBT+Of7it4s6aaa5XP/YuL4cdyWZ3oiIiIiIhqmngToaUlrAwaQtBXwREOi6sP2zcA7+l6XNA6Y\naduSxtleDBzS57YpNcfrl3qy3VF2l8P2fcAONe0+QJUQ3SrpLqolbrcDBwMf6NPf8eWv17o1x5uU\n9iZQ7VA3rv5vHxERERERQ6WeBOgQ4CJgQ0m/BiYBuzUkqkEqCcgLjgdRz7Wf/ZgF3GN7bXg+0ZoF\nHG77kOXo79ly+Nxg60RERERExNAbdAJk+/qyffRGVDMit9le1LDImusTwM69J7YXS7qezOBERERE\nRIxqg06AyizIjlTPzqwMbC8J219sUGzN9EHgQElz+ed22Etsn9PEmCIiIiIiYgXVswTuYuAZqvfn\nLGlMOCOD7ZuotsKOiIiIiIgxpJ4EaD3bmzUskoiIiIiIiAar5/00l5V34kRERERERIxK9cwAXQOc\nX17quYhqIwTbXqMhkUVERERERAyxehKgLwJbA/OWsn10rIAFixbTccSlg75/fl6aGhERERFRl3qW\nwP0V+ONoT34kvVjSKZL2bnYsERERERExvOqZAboL6JZ0GdD7Ys8RvQ22pG2BVwOPU72/6CngPGBz\n4IZhjONgYIrtg4erz4iIiIiIeKF6EqC7y98q5W9Ek9QOHGx7Zs21Y2zfJql7mMP5FvX91hERERER\n0QCD/qfc9tGNDKQBJgPTJP277QfKtc83IxDbTzSj34iIiIiI+Fca7CM9kiYBnwQ2AVbtvW5728aE\ntmIkCbgAeANV4vNl2/8oZUcBDwJrAFsA6wO72f5LKd8LWBeYDvzY9nckvQg4HricajOILakSyB2A\n1YA9gZcAlwDjgLcB1wGXAW8FtrN9aD9xzgZmA7S3T5o+5+TTB/0dp01ec9D3xsjT09NDW1tbs8OI\nYZLxbh0Z69aS8W4tGe/Ro6ura67tGf2V1bMs67vA94GdgQ8DewMPrXh4jWHbknYBPgZ8Bvi4pENs\nn1tueQOwr+1nJO0PfBQ4XNIbgdfYPlDSK4CvAd8BZgDvBq6x/SkASecBb7F9saSLgF9SJUD3AbfZ\n/rGkVamSpBcPEOdpwGkAUzaY6hPnDX5I5u/ZWccvEiNNd3c3nZ2dzQ4jhknGu3VkrFtLxru1ZLzH\nhnp2gVvb9hnAIttX2d4PGJGzP71sL7F9CrABcBZwtqSuUnyF7WfK8W3AOuX4XuAzklYBtgHGl7au\nAuYBV9d0cQuwVin/C/BOqkRxB9vfL9efoZqJioiIiIiIJqsnAVpUPh+QtJOkV1P++R+JJL1G0uoA\ntp+0fSTwBapd4fqtUu69C5gG/DfVErZldtV7YPsG4AfAviWBioiIiIiIEaSeBOgYSWsCnwAOBb4J\njORtnTcCDupzbTzVMrUBSVofOAE4mirBk6QJg+lQ0puB04GLgS/XG3BERERERDRWPbvAXVIOnwC6\nlnbvCHEDsLukrwHXAxOAXwH/oHqeZ1NJfwTuAN5ezjen2tDgpcD+VEvjpgBHSroK6AD2k3Qq0A5s\nBUyV9AtgJvAWqmeOrgCukvQ48O1StrGkTW3/caCAJ44fx23H7TS0v0JERERERDxv0AlQ2QXuQ1RJ\nwPP1yrNAI47tm4F39L0uaRwws2ySMM72YuCQPrdNqTlev9ST7Y6yuxy276Pa3KC3zTOAr1PtAPc3\nqh3hVqZaIncYYMrzRBERERER0Rz17AJ3IdUGAD8FFjcmnMYrCc8LjgdRz7Wf/bS5oJzWtrmoz60L\nBx9pREREREQMtXoSoNVsH96wSCIiIiIiIhqsnk0QLpG0Y8MiiYiIiIiIaLB6EqCPUyVBCyQ9Kekp\nSU82KrCIiIiIiIihVs8ucKsvrVzSJmXjgYiIiIiIiBGpnhmgZTl7CNuKiIiIiIgYckOZAGkI24qI\niIiIiBhyQ5kAvWB76IiIiIiIiJGknm2wo8EWLFpMxxGXDvr++cft1MBoIiIiIiLGnqGcAcpLPiMi\nIiIiYkQbdAKkyvskzSnnUyRt2Vtue6tGBBgRERERETFU6pkB+hqwNfCecv4U8NUhj2iISXqFpFMk\nWdKRkv6r/H1c0h2S1l5K3bUl/VXS+HJ+sqSPD1/0ERERERExlOp5Bui1treQdAOA7cckrdKguIaM\n7TsknQ8caPvY2jJJjwCLl1L3EUkzbS8qlz4H/KNx0UZERERERCPJHtzmbZJ+B7wO+H1JhCYBV9p+\ndSMDHAqSOoFf2Faf66sCi2wPmAQ1mqTZwGyA9vZJ0+ecfPqg606bvGajwoph0NPTQ1tbW7PDiGGS\n8W4dGevWkvFuLRnv0aOrq2uu7Rn9ldUzA/Ql4HxgHUn/A+wGfHoI4msKSTsANwMflzTDdqekacAB\nwMblfBJwPHA0cC+wBzDZ9vGljY8BE4A3AF+1faWklwBnACcCu1AljffantVfHLZPA04DmLLBVJ84\nb/BDMn/Pzvq/eIwY3d3ddHZ2NjuMGCYZ79aRsW4tGe/WkvEeGwb9DJDt7wKfBI4FHgDeafv/NSqw\nRpD07t4/4CCq55gu6S23PQ84t6bKxsD25bgNmAmsVtp6HzDB9gnAV4Ddy31dwM7ASrYPBV4PvLwk\nVxERERER0USDnm6QtBVws+2vlvM1JL3W9u8aFt0Qs/18ciPpsUHcf7WkO8rx45IuBzpK8Vzgbklt\nwJbA+HLfjyTdb/vqcm5JtwJrDemXiYiIiIiIutWzC9zXgZ6a855ybVSyfYXtx4HBPQT1wvq3AjsA\n+wPXDaKKln1LREREREQ0Uj3PAMk1OybYXiKpnvoj1UPAOjXnWwDjllWpzIjtZ/vtkvauLmmC7WeX\nN5CJ48dx23E7LW/1iIiIiIhYhnpmgO6SdKCk8eXv48BdjQpsqEjaEHhzOd5V0nq15bZvAX4j6VpJ\nXwIeBFaStF2fdv4D2A7YorS5HrCRpH2Bx4A3AftJegewtqQDJK0laWtgM2Bm2SAhIiIiIiKapJ4Z\nnA9T7QT3aaplYz+jbN88ws0H5tj+zEA32P5gn0vn9L0FuBPYi2op28q27wR+UHPPRQCSVrK9uqTe\nGbPfUs0qRUREREREkw06AbL9IPDuBsbSEEPwjp9VgAdtL+xtElg40M22l5TP5Xq2KCIiIiIiGqee\nXeAmAR+i2gXt+Xq29xv6sEYGSROBG20vaHYsERERERGx4upZAnchcDXwU2BFZ1VGizcDRzY7iIiI\niIiIGBr1JECr2T68YZGMQLYvWfZdERERERExWtSzC9wlknZsWCQRERERERENVk8C9HGqJGiBpCcl\nPSXpyUYFFhERERERMdTq2QVu9UYGErBg0WI6jrh0wPL5eUlqRERERMQKWWYCJGlj23+S1O+7bGxf\nP/RhRUREREREDL3BzAAdQvXC0xP7KTOw7ZBGNAiSVgL2BDYE7gaeBMYB2wAP2P78cMe0NJJOBu62\nfUqzY4mIiIiIaGXLTIBszy6fXY0PZ9kkrQFcBFxk+6g+ZecDIzHJ+Bzwj2YHERERERHR6ga9CYKk\nmyQdKWnDRgY0CKcCT9r+Yt8C24upNmsYUWw/aLun2XFERERERLQ62R7cjdLLgT3K3xLg+8B5tu9p\nXHgviGEd4AFgH9tnL+W+8cCBwMdsd5SkbW/g/bY7yj07A5sCU4E7bR9b6h0G3A90AFsA6wFvs/33\nUm9rYDPgTuCVwNeBlwLvpZpR+1Gp8zrgF8A1VL/ZZNvH9xPrbKolhrS3T5o+5+TTB/z+0yavuczf\nKEaPnp4e2tramh1GDJOMd+vIWLeWjHdryXiPHl1dXXNtz+ivbNAJ0L9Ukl4BfAbY0/a4FYyvnn63\nBn4DbG/7JzXXVwW6gM2BGcAlwJ+Bc2oSng6guyREU4HjbO9Wkp5bbL9C0uZUCcyZtv9vqXc88Ffb\nX5Yk4A7gVbYXluRlB+AZ4KRS93XAmsC6tn8q6cXAN4A/9V2y19eUDaZ6pVkDr+DLLnBjS3d3N52d\nnc0OI4ZJxrt1ZKxbS8a7tWS8Rw9JAyZA9bwHCEkvl/RJ4FxgY+CTQxBfPR4pnx21F20/Y/syqtmW\nXW2fCdy7lHaeBg4omyl0AuNLOzcCV5e/XrcAa5XjScCLbC8s5/cA42y/1/bvqWZyLgA2tv3T0ubj\nwOV1f9OIiIiIiBhy9TwD9DvgfKrd1na3vaXt/naGaxjbtwM3APtLWtbM04BTW7YfANYGjgNuHETX\nKvUeBO6WtEG5vhXw85p2LwNuAmYNos2IiIiIiBhm9cwAvd/2FraPtX1XwyJatr2onrH5hqS+u9hN\nBRaU40eANcoSN4DpVMkbklYHzgM+C0ysLmnlMiO0LHOAQyS9GbihdmtrSe8CDgIelvSp5fp2ERER\nERHRMIN5D1Cvv0n6IvDGcn4V8H9sPzH0YQ3M9s2SNgU+AXxP0m+A+4DVgP8Edi739Ug6BbhO0rXA\nhcBjknYHrgXagY8Avwd6qLbP/g4wDdhD0n2ly22BdctzQytTzRrtavsvvTFJmgR8mCoB+xXwA+AK\nSc8AVwDbUSVjG9q+c6DvNnH8OG7Lcz4REREREQ1TTwL0LeCP/HN5117At4F3DXVQy2L7YeDIforO\n6nPf0cDRNZcuqTlet+Z4E6imgWxPL5sd4GqHiPfXtinpG8AfJN1NtRvevcDhwBeA56iWy/0aWKX8\nmeq3EvX93hERERERMcTq+Yd8Q9u71pwfLekPQx1QM5WE5/nPviR1Um2I0G57cUmU3ggcY3v3fqo8\nW9s8sLCfeyIiIiIiYpjU8wzQAknb9J5Iej3/fN6mVXyUaivtxfB8onQj8NumRhUREREREYNSzwzQ\nh4HvSOp9G+djVC8XbSWHAR+WNIXquaElwASqdwBFRERERMQIN6gEqOyOtpHtzSWtAWD7yYZGNgKV\njQ/6e/YoIiIiIiJGgUEtgbO9hPLSU9tPtmLyExERERERo189zwD9VNKhkl4maa3ev4ZFFhERERER\nMcTqeQZoD6qdzD7a5/oGQxdORERERERE49STAL2KKvnZhioRuhr4RiOCioiIiIiIaIR6EqCzgCeB\nL5Xz95ZrswasEXVZsGgxHUdcOmD5/ON2GsZoIiIiIiLGnnoSoE1tv6rm/BeSbhnoZknjgJVsLyrH\n42wvLGWrAIvLy0RXtf3MAG18ADjW9jp1xBkREREREdGvejZBuF7SVr0nkl4LXLeU+ycCe0kysCuw\ndk3ZesB5kq4BXruUNr5VR3zLTdKver+bpHdJ+uFw9BsREREREcOrnhmg6cBvJN1TzqcAt0maB9j2\nZrU32+6R9PNyfF6fsrtKvadsXzVQh7Yt6R91xLi8ZgN/LseXAb8dhj4jIiIiImKY1ZMA7dCwKJrM\n9i01xwuABU0MJyIiIiIiGmTQCZDtvzQqiPKM0HuAx4FJwIbAZ2y7z33rUs3W/A5YBdgaOMH2o5Je\nApwBnAjsArwOuNf2rJr6+5Q+BCyxfaGkVYEPAw/bPqcshfuQ7Q+UOjsDmwJTgTttHytpPHAYcD/Q\nAWxBtazvbbb/XuptDWwG3Am8Evh63+9T7ptdvhPt7ZOYM+25AX+n7u7uZf6WMXr09PRkTFtIxrt1\nZKxbS8a7tWS8x4Z6ZoCWm6QP93N5BvBwOT6wxPIw8ADwamAycG9NGysBFwL72L61XHsU+C7wNqAL\n2Bk4yfahkgRcI2ma7XmSXgW8x/ZbS91zJG0PrAWsC5xV6ryJKgFD0tTS324l6bkFOJZqS/APAGfa\nPqrcezzVjnhfLu2cDbzK9kJJGwA/lPQM8H7bz2c5tk8DTgOYssFUnzhv4CGZv2fnUn7lGG26u7vp\n7OxsdhgxTDLerSNj3Voy3q0l4z02DEsCZPsF7wsqszkd5XQWsK/tP5Xzy/tpZiNgvd7kp7T7a0mv\nl/Rvtn8k6X7bV5cyS7qVKsGBahbn0Zr27gX+bvskSUfV1Pk+VUIF8DRwQEm+OoHx5b4bJV1N9S6k\nXrcALy/Hk4AX9e56B9xDtQvee/v/hSIiIiIiYjjUswtcI00ANlnGPUuA/taHmWo53EBUPq8Gpkrq\nTfqmA79cWoe2H6Dave444MZlxPd8X7YfBO4uMz8AWwE/H0T9iIiIiIhooGGZARqES4E5krptPyJp\nCrC67Ztr7rkDuF/SK23fDiBpG+A6238dRB8PUb249XBJNwFH2p67tAqSVgfOA14DrFNd0spUydiy\nzAEOkXQ+cIPtC5dVYeL4cdyWl51GRERERDRMwxIgSRtRLW1D0u7A5bafKufTqJ4BepmkHYHPUW0i\ncKOk64CfAN+S9D5gbUl7A98H3gV8pNyzEtUszu6lzXeUew8A/pdqydxmwExJNwJ7AP8JfML2EwPE\n/G8l5inlPUd/A9qBjwC/B3qAU4DvANOAPSTdV6pvC6xbnhtamWrWaNdGbh4RERERERH1aeQM0F+o\nEptjgFWBhTVlfwbeSTWTMh5YZHvffto4p/z1eoBqZqXXBTXHF9teXZLKbmu/pdqdDQBJZ1AlTH+S\ndC/VcrW5wCHlFlM9I3Qi8AVgFdvPUm2Q0GuT0pZsTy+bHVD6e39t4JK+AfxB0t3le94LfLJ39ioi\nIiIiIoZfwxIg28/UnC7oU1Z7/uwQ9bekfL5gq+nio8D5tj8EUHZ1O4RqN7fVgPttLxpMXL19DNSX\npE6qzRfabS8uidIbgf+hzFhFRERERMTwGymbIAyHjwFX9p6UZOd64AbgJUD3EPb1UaDb9uLSl6k2\nUfjtEPYRERERERF1GimbIAyHDwL/Lel6/rkcrwd4Cvhyn9mfFXUY8OGymUMP1RK4CcBJQ9hHRERE\nRETUqWUSINvdDO0sz9L6+gtw5HD0FRERERERg9dKS+AiIiIiIqLFJQGKiIiIiIiWkQQoIiIiIiJa\nRss8AzQaLFi0mI4jLh2wfP5xOw1jNBERERERY8+ongGSNK58StIqNdfV+5LS2usREREREdHaRm0C\nVJKfnSTdT/WOndfVFE8AdpZ0O5Bpk4iIiIiIAEbxErjyktGLJD0C/Ax4uqbsGUmLgffYntusGCMi\nIiIiYmQZtTNAvWz/GvgicJakVQEkvQxYM8lPRERERETUku1mx7DCJI0Hfkc1E3QEcIDtL5Wy7YAL\ngE2Bx4B3AKcC/2F7vqQdga2AR4HpwGuBD9m+StKLgOOBy4GtgS2pZs12KLNMbcAngAXAW4G9bN8v\n6ZXAJ4GfAJ3AG4EzbH+xn9hnA7MB2tsnTZ9z8ukDfs9pk9dc7t8oRp6enh7a2tqaHUYMk4x368hY\nt5aMd2vJeI8eXV1dc23P6K9sTCRAAJL+A/g98A3gGNuP15TNBzptz689B3qAc4BFwCzbC0pC9AHb\nu0p6E/Aj4CDbZ5e65wFn275Y0jeBb9i+TtL/ALfY/q6kE4BdgTfZvkfS2sBNticv7TtM2WCqV5p1\nyoDl2QVubOnu7qazs7PZYcQwyXi3jox1a8l4t5aM9+ghacAEaNQvgetl+1bg28DqtcnPMuo8DJwL\nzLW9oFy+BVirlF8FzAOurqn2fDnw1ZL8rAe8Ehhfrn8F+Ivte0o7j1AlWRERERER0USjdhOEATwC\ntPdzvd5pLg2y/A+SDgPuBm6us4+IiIiIiBhmY2YGaBkeAtYBKM/ntAHjhqDdQ6mWEf4AeHnVvCYM\nQbsREREREdEAY2IGqGxG8FZgB6BN0vuAy8sSN4CjqHaJmwecDdwKzJL0PWBbYIqkbcr13YANJb0e\nWAXoAPaTdCrV7NJWwFRJVwIvBaZJugf4A3Aw8DCwUblnFnA+1buI2iXtBZzjAR68mjh+HLflOZ+I\niIiIiIYZEwmQ7R7gh+Wvv/IfAz+uuXQxVNM1wN62LUklMTmh/FGudZT7sH0fVZLV6+A+XZ1S6l1i\n+4SaNi+gmnWKiIiIiIgmGhMJ0PKqnYnpb1am99pAMzbLarfeehERERER0Vit8gxQREREREREEqCI\niIiIiGgdSYAiIiIiIqJlJAGKiIiIiIiWkQQoIiIiIiJaRhKgiIiIiIhoGUmAIiIiIiKiZbTMe4Ak\njQNWsr2oHI+zvbCUrQIstr1Y0qq2nxmgjUOBbW3v2IgYFyxaTMcRl/ZbNv+4nRrRZURERERES2ml\nGaCJwF6SDOwKrF1Tth5wnqRrgNcupY0LgbfV27GkLSVdW2+9iIiIiIgYWi0zA2S7R9LPy/F5fcru\nkjQPeMr2VUtp4w5Jy9P99cBuy1MxIiIiIiKGTsskQM1k+zngnmbHERERERHR6mS72TEMG0kdwN22\nXzCNI+kooMP2PuUZofcAjwOTgA2Bz9h2WUL3HuClwHbA7cBh5dmi1YBZwCNUy+pWs32ipFcBR9ve\nvZ9+ZwOzAdrbJ02fc/Lp/cY+bfKaK/LVYwTq6emhra2t2WHEMMl4t46MdWvJeLeWjPfo0dXVNdf2\njP7KWnIGSNKH+7k8A3i4HB9I9ds8DDwAvBqYDNwLYPvc0s6XgJ8DBwPHA8cCc4FFwHxgV0mrApsB\nr+kvFtunAacBTNlgqk+c1/+QzN+zs67vGCNfd3c3nZ2dzQ4jhknGu3VkrFtLxru1ZLzHhpZMgGx/\no+81SesCHeV0FrCv7T+V88sHaOc5SacC+1MlQLOAw2t2kbusfJ4r6bghCj8iIiIiIpZTK+0CV48J\nwCaDvPcJ4B/LUS8iIiIiIoZZEqD+XQrMkbQ2gKQpkp5PbCS9pObeLuC7NfWOlTSx3LeZpMnDFHNE\nRERERCxDyyyBk7QR1RI1JO0OXG77qXI+jeoZoJdJ2hH4HNUmBjdKug74ie2v1jR3gaSLgDbgTttn\nl+sHAWcAt5V3Cv0IuEzSXsBLJG1n+6cDxThx/DhuywtPIyIiIiIapmUSIOAvVInNMcCqwMKasj8D\n7wSWAOOBRbb37a+R/naQqyl7pLTzPEkrA/8LnAOssgLxR0RERETECmqZBKhmYwKABX3Kas+fHeJ+\nn2tU2xERERERUZ88AxQRERERES0jCVBERERERLSMJEAREREREdEykgBFRERERETLSAIUEREREREt\nIwlQRERERES0jCRAERERERHRMlrmPUCjwYJFi+k44tJ/uTb/uJ2aFE1ERERExNgzKmeAJI1rdgwR\nERERETH6jIoESNI0SZ+VZEmfBWb0Kd9S0rUNjuFgSSc1so+IiIiIiGisUbEEzvY8SU8BRwFn2Z7f\n55brgd0aHMa3GCW/V0RERERE9G9M/ENv+zngngb38UQj24+IiIiIiMaT7WbHMCiSOoC7gfX7zgBJ\nehVwtO3dy/lrgbcCLwZWtf3Rcn1dYDbwO2AVYGvgBNuPSnoJcAZwIrAL8DrgXtuzJKm0t53tQyW9\nCDgeuLy0sSVVMrmD7WdKXzOBNYBHgXVsnzXA95pdYqK9fdL0OSef/i/l0yavuTw/V4wCPT09tLW1\nNTuMGCYZ79aRsW4tGe/WkvEePbq6uubantFf2ZiYAQI2A14DUBKZ42x3lfP55XMl4EJgH9u3lmuP\nAt8F3gZ0ATsDJ5UkR8A1kqYBdwA7UCVUUD2D9G7gGtufKm2dB7wFuFjSWsAxtjcvZZ+T9G1goe39\nawO3fRpwGsCUDab6xHn/OiTz9+wcit8nRqDu7m46OzubHUYMk4x368hYt5aMd2vJeI8No2IThGWx\nfW7tKbAfgKRtgNXK9Y2A9XqTn1Lv18DrJf2b7R8B99u+upQZuBVYq8zqXFBT7ypgHnB1Tb+3AGuV\n46nAP2rK7gGe7Jv8RERERETE8BoTCVBZ2gaA7ceBRZJOAO7nn4nIEuC5fqqbajncgM3XE0r5vAlY\nTdIa5Xwr4Od1tBMREREREQ0w6pfASZoM7FFzLuDHwPZUyc+Ly/K3+cD9kl5p+/Zy7zbAdbb/OsRh\nPQscC3xa0k+Bs23/bIj7iIiIiIiIOo2KBEjSDODN5XSmpL8C44CXAocAc4CXSNoO+DXVszoHAL8C\nrgH+F/gQ8C7gI5Kuo5r9mg70bpzwDmBtSQeU+zeierZopqQngJnAxpI2BSYBHcB+kk4F2qlmeaZK\nurLU2wvY1/aDg/2eE8eP47bjdqr/B4qIiIiIiEEZFQmQ7euA64DP9y2T9PVyeA6wiu1ngSk1t1xR\nc/wkVbLU64Ka44ttry5J5fmf3wJblD5WAQ6jWi43HrjZdkeZbcL2fVSbJPTG9ABVQnSrpLuolsbd\nDhxs++/1fv+IiIiIiBgaoyIBWpryDqBez65AO0vK5wv2Bbe9sOZ0Yc31gfYQnwXcY3ttAEnjyrXD\nqWasIiIiIiKiCUZ9AjRCfYJqS20AbC+WdD3Vsr2IiIiIiGiSJECN8UHgQElzqdmFzvY5TYwpIiIi\nIqLlJQFqANs3UW2FHRERERERI8iYeA9QRERERETEYCQBioiIiIiIlpEEKCIiIiIiWkaeARpBFixa\nTMcRlz5/Pj8vRY2IiIiIGFKZAYqIiIiIiJYx5hIgSftI2nQp5Z+UtPpwxhQRERERESPDWFwC91Zg\nF0lXAUuAOcDlwLXABKp39LxU0t22T1neTiQdBzxs+wRJk4FfAa+0vWiFv0FERERERDTEWEyAfmn7\n670nkg4CrrTSzE/FAAAgAElEQVR9Zjn/A3Ar8OgK9vMV4NlyfD/w5iQ/EREREREjm2w3O4aGkjQf\nOKo3ARppJM0GZgO0t0+aPufk058vmzZ5zWaFFcOgp6eHtra2ZocRwyTj3Toy1q0l491aMt6jR1dX\n11zbM/orG4szQEslaWVgD2Cy7ePLtY9RLY97A/BV21dKeglwBnAisAvwOuBe27NKnR2oZn0Ok/Ry\n4Ou2dyxlOwJbUc0yTQdeC3zI9lV947F9GnAawJQNpvrEef8ckvl7dg79DxAjRnd3N52dnc0OI4ZJ\nxrt1ZKxbS8a7tWS8x4YxtwnCILQBM4HVACS9D5hg+wSqZW27l/u6gJ2BlWwfCrweeLmkaWUThZnA\npHJvB7Btaa8dOBB4NXCq7b2Ag8q1iIiIiIhoopZLgGw/TrUpQq+5wFcktQFbAuPLfT8C7rd9dTk3\n1bNDa9l+Cvh/NW1eBfytHD8MnAvMtb2g3HILsFYjv1dERERERCxbyy2B68v2rZLeCWwIXAe8YhlV\ntJxdLW+9iIiIiIgYIq2QAC018ZC0FbCf7bdL2ru6pAm2n11avUaYOH4ctx2303B3GxERERHRMsZs\nAlRehroTsB6wl6SngR8CGwHbAWtI2rCUbyRpX+AR4E3AfpLuB9aWdADwv6XeZsBMSTfW9DOR6t1D\n7ZJ2Aa6neh5oiqRtqJbN7QZsKOn1tn89DF8/IiIiIiL6MWYTIOBm4Gbbn6+9KOlOYC+qmaGVbd8J\n/KDmlovKfSvZXl2SyvM/vwW2qGkHwFTvAroUWJ3q+aFFwN62XVP3hPIXERERERFNNGYTIA/wgiPb\nC3sPgYX93VPuW7K0dqh2kbu/3LekXPuX9pZSNyIiIiIimqDldoEbQpsBZzc7iIiIiIiIGLwkQMtB\n0iTgD7b/1OxYIiIiIiJi8MbsErhGsv0Q//ouoYiIiIiIGAUyAxQRERERES0jCVBERERERLSMJEAR\nEREREdEy8gzQCLJg0WI6jrj0+fP5x+3UxGgiIiIiIsaezABFRERERETLaIkZIEkrAXsCGwJ3A08C\n44BtgAdsf76J4UVERERExDAZ8wmQpDWAi4CLbB/Vp+x84JRmxBUREREREcOvFZbAnQo8afuLfQts\nLwY+PvwhRUREREREM8h2s2NoGEnrAA8A+9g+exn3jgM+CSwC3gJ80vaNkl4KnACcDewAvBH4he1D\nSr09gBeXv3bbh0l6D/A925L078CuwJdtq59+ZwOzAdrbJ02fc/Lpz5dNm7zmCn3/GNl6enpoa2tr\ndhgxTDLerSNj3Voy3q0l4z16dHV1zbU9o7+ysZ4AbQ38Btje9k9qrq8KdAGbAzOAS4D1gD/Z/oGk\nDwHr2P4fSf8FHANsY/uPklYB/gxsavtJSTcBO9i+X9KbbF9V+nBtwtP3vD9TNpjqlWb9c0VedoEb\n27q7u+ns7Gx2GDFMMt6tI2PdWjLerSXjPXpIGjABGutL4B4pnx21F20/Y/sy4BpgV9tnUj0n9CNJ\na1MlRuPLvV8BHrf9x3K+ELgLeElp7gzgd5I+BdzQ0G8TERERERErZEwnQLZvp0pK9i9L3JZ2703A\nfsAuDC6R6Z3N+RLVsrj1gKuX1U9ERERERDTPmN8FDtgL+BnwDUkfsf1cTdlUYAGApN2BLWx/VNJn\nq0uaYPvZZbR/kO2TgI9KuhhoA54AHpK0ju0HJU0vfYwrGy/0a+L4cdyWZW8REREREQ0zpmeAAGzf\nDGwKPAx8T9JBknaXtDfwn8DO5db1gC0lvY9qidt7gbeX83ZJe0uaKOktwAbALEkTgZdJ+qykdwLf\nt/1Eae9TwC8kfQeYSPXc0OzMEEVERERENE8rzABh+2HgyH6Kzqq55yTgpJqys6GaBrJ9Tvk08BNg\nSs19hwzQ5zeBb9ZcesVyhh8REREREUNkzM8AraiS9Dz/GRERERERo1cSoIiIiIiIaBlJgCIiIiIi\nomUkAYqIiIiIiJaRBCgiIiIiIlpGEqCIiIiIiGgZSYAiIiIiIqJlJAEaQRYsWkzHEZfSccSlzQ4l\nIiIiImJMSgIUEREREREtY+VmBzCUJK0E7AlsCNwNPAmMA7YBHrD9+UG08Xvgo7Z/38hYIyIiIiJi\n+I2ZBEjSGsBFwEW2j+pTdj5wyiCb2h24Z2iji4iIiIiIkWDMJEDAqcCTtr/Yt8D2YkkfH0wjtucP\ndWARERERETEyyHazY1hhktYBHgD2sX32Uu4bDxwIfMx2h6QNgb2B95fzNYAjgcttXyXp3cDGwJ+o\nnpd6O/Dftu+UNAPoAm4EJgEvBb4IrAZ8Fphhu1PSNOAAYGPbnf3ENBuYDdDePmn6nJNPB2Da5DVX\n9GeJEa6np4e2trZmhxHDJOPdOjLWrSXj3Voy3qNHV1fXXNsz+isbKzNAG1IlKH+rvShpVaokZXNg\nBnAJ8DvgYwAlkfkW8P5SZRIwE7iinD/Wu5xO0ueBh0qd9YBvA1vYXlTK/xs41PbnJV1S+sP2PEnn\nAkf1F7jt04DTAKZsMNUnzquGZP6encv/a8So0N3dTWdnZ7PDiGGS8W4dGevWkvFuLRnvsWGs7AL3\nSPnsqL1o+xnblwHXALvaPhO4d6BGbN8JXFdzfgWApPcDWwGHlKKZwE29yU9xObDPinyJiIiIiIho\nrDGRANm+HbgB2F/SuGXdXk/bkl4HzAF2r0l4lgDP9bl1CbDK8vQRERERERHDY0wkQMVewHrANyT1\nXdo3FVhQjh8B1ijPAwFMp9oq+wUkTQH+F3iP7QclrSvptVRL6TaraQNgJ+DMcvwQsE5N2RYD9RER\nEREREcNnrDwDhO2bJW0KfAL4nqTfAPdRbUrwn8DO5b4eSacA10m6FrgQeEzS7sDfqZ4XerOk24GL\ngXnAJpK2BD4A7Gz7fkn7A4dJuhFoB56mbLVt+xZJvyntXwNcC6wkaTvbPx3oO0wcP47bjttpqH+a\niIiIiIgoxkwCBGD7Yapd3Po6q899RwNH11y6BEDSBGpma2xv3qedr9a0cS1VYjNQLB/sc+mcZYQf\nERERERENNqYSoBVl+9ly2Pf5noiIiIiIGAPG0jNAERERERERS5UEKCIiIiIiWkYSoIiIiIiIaBlJ\ngCIiIiIiomUkAYqIiIiIiJaRBCgiIiIiIlpGEqCIiIiIiGgZTU+AJI2TpHI8vtnxNNOCRYvpOOJS\nOo64tNmhRERERESMScOSAEnaXtLFkn4pafU+xWsDO0r6ITBtKW1MlnR3qydJERERERGx/FYejk5s\nXynJwJnAJZJ2sL2glD0IXCppku3rl9LM/cCbbS9qfMQRERERETEWDecSuEXALlQzPhdImlBPZVfu\nakhkERERERHREmR7eDqSOoH5wNPAz4C7gN1sP1fK97F9pqRxwHuAx4FJwIbAZ4ApwNdt7yhpLeBT\nwAPAWsDmQAfwPuDdwEbAZGCW7fml/R2AVYFVgG2Ao4CngMOoZpc6gC2A9YC32f57qbc1sBlwJ/DK\nEoN7Yy5xClhi+0JJrwLOAb5Uvs87gf8BvmD7zH5+l9nAbID29knT55x8OgDTJq9Z/48co0pPTw9t\nbW3NDiOGSca7dWSsW0vGu7VkvEePrq6uubZn9Fc2LEvgatl+SNK2VEnQOZLea3tJzS0Hlrgepkpw\nXk2VzHQA25Z7ngZeCrQBH7FtSV+hSoreY3uxpI8BHwEOlzSDKjE6F3gGeBCYXj4/AJxp+ygASccD\ns4Avl80ZzgZeZXuhpA2AH0p6Bjiu9PXWUu8cSdsDTwA31XzfC0oSNNDvcRpwGsCUDab6xHnVkMzf\ns3PwP2qMSt3d3XR2djY7jBgmGe/WkbFuLRnv1pLxHhuGPQECsP1wTRL0TUkfqCmeBexr+0/l/PLy\nea+kv5X6z0q6HZjvf05hXQ9Msb24nP+RakYHYFfgGtuX92kTSVcDV9f0fwvw8nI8CXiR7YXl/B5g\nnO33SpoFPFpT717g77ZPknTmoH+MiIiIiIgYNk3bBtv2I8CbqWZ4vlxTNAHYZDmaXNLn3FRL05an\nTZUYHwTuLjM/AFsBPy/HVwNTJfUmkdOBX9b0HRERERERI0xT3wNUkwS9jvIcDHApMEfS2gCSpkha\nnoSo1qXAPpL+s7Q5sTyTNBhzgEMkvRm4wfYp5fpDwFlUS+xmAkfanltTtk7pa02q55jGreB3iIiI\niIiIFTQsS+BK8rAPcIeka2xf2Vtm+9FSfnq59DmqjQhulHQd8BPgW+U5mnZJuwDXAa8H/qMsYZsA\n7AZMlDSN6tme3YCNJK1v+2eSjgIulnQHcC1wjKTXUL17aA9J95X+twX+f3v3Hmd1Ve9//PVmQFAH\nSRhOJhzj5gW5g4JHjzJc0tRThiJ58hKp+FM7mWF1MH6av/NLf+TxAlFRmJfymkIipZWl4iVviQgq\n6BF1IrS84I0xiAE+vz++a2g7zMAAm9mz934/H495zP6utb7ftfZe8x3mw7p895LUh+zzmQacEBF/\navC2zgQGAxdExPsN8n4I/CIFWb8FFgMHS7o3Iv7c1Oe0a7sKXpx27FY+TTMzMzMz214t9Ryg+8jW\n+zSV/y5ZwEJ6PtCXcvMltSEbxekItCObonYs2bS3inR8fDpuS7bl9ldTekW67pXAlQ2u+1REDEub\nHZDWE53WoMyPgGckvZquvxL4JnAt2bS3FyStTHUtBCanneeGYmZmZmZmrUpBNkHYVmmXuPo1Pusa\nZK/fxuPc60bu94bSCE5noCrtLCfgCLJtrR8B7oyISalsO2Ay2a5y39vKWzIzMzMzswIoigCogM4F\nrqjfWS5tt70YeAz4CnBAfcGIqJP0NNk222ZmZmZm1go5ANqybwBnS9oHqCUbhWoPXE227fbUFPTU\nj0rVRsQfCtJSMzMzMzPbKgdAW5A2PriwiewF6cvMzMzMzIpEQbfBNjMzMzMza0kOgMzMzMzMrGw4\nADIzMzMzs7LhAMjMzMzMzMqGA6BWZE3dBnpMubvQzTAzMzMzK1kOgJogqSLnddsGeXtIulHSNS3f\nMjMzMzMz214OgJrWU9JXJa0HjpbUTlKNpL0j4gPg50A7AEndJL0qqV1BW2xmZmZmZlvkAKgJEbEc\nuAtYGxG/jIg6YHREvJ6K1OYUfx0Yk8qYmZmZmVkr5QehboOIeKWJ9AAazTMzMzMzs9ZD2d/u1hhJ\nPYDnIqJS0j8BlwOXRESNpGpgYkRMlPRJYFZEHJPOOwY4BHgHGAaMACZFxION1HEWcBZAVVXXYRdP\nv4YB3Trt/DdnBVdbW0tlZWWhm2EtxP1dPtzX5cX9XV7c38Vj1KhRCyPioMbyPALUfHsDnwYuaSSv\nBzAaQFIVcB5QB0yIiDUpIDoP2CwAiojZwGyAfXr1iSufbUvNydU7ofnW2ixYsIDq6upCN8NaiPu7\nfLivy4v7u7y4v0uDA6BmiohnJL3QRN6Dkv6aXr8t6TagR0SsSUWWAp1bqKlmZmZmZtYEb4LQclTo\nBpiZmZmZlTsHQFvnRVJmZmZmZiXCAdCWCfhAUhtJRwG9gWMlDQROAAZIOkzS54AqSePShgijgWpJ\n/yqpCzAe6C3psC1Vtmu7CmqmHbtz35GZmZmZWRnzGqAtawusjIiNkh4A9klpGyPiKwCS2gAVQEey\nB6PWAV+MiJCktEX2FenLzMzMzMwKyAHQlu0B/AogItaltI887DQiNgIb0+G6BnmePmdmZmZm1op4\nClwDkiokdU2Hw4CfFLI9ZmZmZmaWPw6ANjcQeF7S/yZ7COpfCt0gMzMzMzPLD0+BayAiFgH/VOh2\nmJmZmZlZ/nkEyMzMzMzMyoYDIDMzMzMzKxsOgMzMzMzMrGw4AGpF1tRtoMeUuwvdDDMzMzOzklWy\nAVDazlrpdbtCt8fMzMzMzAqvqAMgSUdK+qWkhyR1bJDdBThG0lxggKTj0+ud2Z7pkr66M+swMzMz\nM7PtV9TbYEfEvZICuAH4laRPR8SalPcmcLekrhHxtKRlwGM7uUmXAX/byXWYmZmZmdl2KuoRoKQO\nGEc24jNPUvvGCkXEmp39UNOIeDMiandmHWZmZmZmtv0UEYVuww6RVA3UAB8C9wGvAOMjYn3KnxgR\nN0g6BJgUEWekNUHfAF4HegBDge7A0RHxRjrvX4CBwMvAfsAsYG/gC2QjZ79I5xwKPAA8Dnwe6BYR\nl6drfAVoDxwO/CAi7m2k/WcBZwFUVXUddvH0axjQrVMePyFrrWpra6msrCx0M6yFuL/Lh/u6vLi/\ny4v7u3iMGjVqYUQc1FheUU+ByxURb0kaTRYE3STpCxGxESBthjAS6J2KHwicAdwQEZekMpcDE4CZ\nqfyNwIERsU5SL2AusBa4miz4uQl4A3gsIh6R9DHgM8AL6XqnAO0j4gpJi9O1NwuAImI2MBtgn159\n4spn21JzcnV+PxxrlRYsWEB1dXWhm2EtxP1dPtzX5cX9XV7c36WhFKbAbRIRbwOjgQOAn9TvAhfZ\nMNfPc8otBh5OX/WWAp3T667A7hGxLh2vACoi4gsR8UeyEZt5wAER8ft0zfeA3+RcbyHwfUmVwHDA\nO9GZmZmZmRVYSQVAABGxChgDDAFmbuPp9QHTm8CraeQH4BDg/pw6fg0sIRvVaaody4BPA/8LeGob\n22FmZmZmZjtByQVA8JEg6FDS+prtcDEwWdIYYFFEzKjPkHQ8cD7wtqRvNXZyWnN0ekRcCeyVJTW+\nQYOZmZmZmbWMol4DlIKTicBLkh7P3WQgIt5J+ddI+jjZaM0+kkYAG4EBwOclvZZOGQ3sJakP2ecy\nDTghIv6UU19X4GygD/AIMAf4raS1wG+BscAeknqTbZCwv6QvAavI1iCdTraZQqN2bVfBi9OO3dGP\nxczMzMzMmlDUAVBE3Ee26UFT+e8C49Oub1cC/w3sAqyLiGEN1gidlnuupB8Bz0h6lSxgWgn8Z7rG\nerLpcn9I19sFCODUlN42Il4mC5Dqzd/hN2xmZmZmZjukqAOg5oqIupzDv+ekN7oHeNpauzNQFREb\nUqB0BPCdiDixkVP+nvM6gHWNlDEzMzMzswIryTVAeXAusCAiNsCmQGkx8FhBW2VmZmZmZjukLEaA\ntsM3gLMl7QPUkk2Ba0/2DCAzMzMzMytSDoAakTY+uLDQ7TAzMzMzs/zyFDgzMzMzMysbDoDMzMzM\nzKxsOAAyMzMzM7Oy4QDIzMzMzMzKhgOgVmRN3QZ6TLm70M0wMzMzMytZRR8ASapI39tKapNeF/37\nMjMzMzOz/Cu6QEHS4ZKulRSSfgQMSFl9geslLQGOl3SCpLnNvOaxku7KOf6jpIPz33ozMzMzMyuk\nonsOUEQ8LOkPQDdgr4h4JqU/K+k14IKIeFvSrsCjzbzsAuClnOMTgRV5bLaZmZmZmbUCRTcCBBAR\nG4FTgYMknQ8g6Wzg9oh4O5VZExF/aeb1PoyI/8k5rkl1mJmZmZlZCVFEFLoN203S4cBvgW8Df46I\n23LyDgEmRcQZktoB3wBeB3oAQ4HuwNER8YakA4FLImKCpD2AC4HfRMSDkiqBC4A1wFHAqRHxuqT9\ngG8CvwOqgSOAayPiqlR/Rcp/MtX5eEQ838h7OAs4C6Cqquuwi6dfw4BunfL5MVkrVVtbS2VlZaGb\nYS3E/V0+3Nflxf1dXtzfxWPUqFELI+KgxvKKbgpcrjQd7kpgKnBAfbokASOB3inpQOAM4IaIuCSV\nuRyYAMwEDgGGp7Jdgc+QBVYA04EfRcRTkjoBo4CbyYKWMcB/RcTPJXUBlgBXpfMmAW0i4r60KcOz\nku4BFkfETTnvYTYwG2CfXn3iymfbUnNydT4+HmvlFixYQHV1daGbYS3E/V0+3Nflxf1dXtzfpaEo\np8DVS+t8AOYDd6SRHiIb1vp5fbmIWAw8nL7qLQU6p/zrcsq+DDyVU+4HKfjpDuwHtEvp3wf+FBEr\n0nmrgLqc8wYC9dPxNgKrgVtygx8zMzMzM2tZRR0AkU1VuxI4myyYuXobz1czyjwj6Rtko0SbTWHb\ngl8BIwDSyFEl8D9bPMPMzMzMzHaqog2AJH0NmBMR70XE34DxwERJE/Nc1dfJ1krNAT6ZVa32zTjv\nEWC1pC8AxwCfiogP89w2MzMzMzPbBkW3BkjSKGAccDrwtqQPIqIG2Bt4Fpgt6eOp+D6SRgAbyZ4X\n9Pm0VTbAaGAvSX0iYnnO9Y8ABgFj0jOF9gYGSFoBPAN8jWxq2/5AH0kTgDuBY4EqSacCN5Gt67mP\nLEhb15z3tmu7Cl6cdux2fS5mZmZmtu3q6upYuXIla9eu3WrZTp06sWzZshZolTVXhw4d6N69O+3a\ntdt64aToAqCIeAB4ADgvbS6glH4fWcBBWgu0Ebgc2AVYFxHD0uYI9WuETmt46fT9CbJd4ipS2a81\nKDcj1fGriLhCktL15pFNcyPln0e2NmmKpFUp+faIuGIHPwIzMzMzy5OVK1fSsWNHevToQfpTsUmr\nV6+mY8eOLdQy25qIYNWqVaxcuZKePXs2+7yinQIH2eYCEbGhkfS6iNgQmb+nAIV0vNm+35J2I9si\nm/ryEbE+ItZvoe7I/d7gem2Bb5Ftmd07IoYDY4FDJQ3czrdrZmZmZnm2du1aunTpstXgx1ofSXTp\n0qVZo3e5ijoAyqODgGvzeL39gP0i4qX6hIj4APgD8Kc81mNmZmZmO8jBT/Hanr4ruilw+ZamxXXP\n3Qp7R0XEUknzJf0H8Aqwnmz77Lsj4v181WNmZmZmZtum7AOgNIXtlp1w3R/l+5pmZmZmtnP1mHJ3\nXq9X4w2uWh1PgTMzMzMzs2Z54YUXGDx4MEOGDOHll1/m0EMPbZF6q6ureeqpp/JyLQdAZmZmZmbW\nLPPmzWP8+PEsWrSI3r178+ijj25WZv36JvcRaxUcAJmZmZmZFdDPfvYzBg4cyKBBgzj11FOZOHEi\nc+bM2ZRfWZk9aWXBggWMHDmS4447jl69ejFlyhRuvvlmhg8fzoABA3j55ZebrOONN95g3LhxDBo0\niEGDBm0KXK666ir69+9P//79mT59OgA1NTX07duXSZMm0a9fP4488kjWrFnDPffcw/Tp05k1axaj\nRo3arG2HH344n/3sZznwwAOpqanhgAMOYOLEiey3336cfPLJ/P73v+ewww5j33335cknnwTgww8/\n5PTTT2f48OEMGTKEu+66C4A1a9Zw0kkn0bdvX8aNG8eaNWvy9nmX/Rqg1mRN3WY7epuZmZlZCXv+\n+ef5zne+w6OPPkpVVRXvvPMOkydPbrL84sWLWbZsGZ07d6ZXr16ceeaZPPnkk8yYMYOZM2duCmIa\nOu+88xg5ciR33nknGzZsoLa2loULF3L99dfzxBNPEBGMGDGCkSNHsueee/LSSy9x6623cs011zBh\nwgTmzp3LKaecwtlnn01lZSVf//rXN6vj6aef5rnnnqNnz57U1NSwfPly7rjjDq677joOPvhgbrnl\nFh555BHmz5/PZZddxrx587j00ksZPXo01113He+99x7Dhw9n7Nix/PjHP2a33XZj2bJlLFmyhKFD\nh+btM/cIUDNJaiPpc5J+Uei2mJmZmVlpuP/++znxxBOpqqoCoHPnzlssf/DBB/OJT3yC9u3b07t3\nb4488kgABgwYQE1NzRbrOeeccwCoqKigU6dOPPLII4wbN47dd9+dyspKjj/+eB5++GEAevbsyeDB\ngwEYNmzYFq9db/jw4R95IGnPnj0ZMGAAbdq0oV+/fowZMwZJH2nrvffey7Rp0xg8eDDV1dWsXbuW\nFStW8NBDD3HKKacAMHDgQAYOzN+jNIt+BChtY30asBvwV6AS6Ac8FRFzUpnhwPfTA0m3125Af2DL\nP5WNt3E68GpEzNiB+s3MzMysDLRt25aNGzcCsHHjRtatW7cpr3379ptet2nTZtNxmzZt8rr2Jree\nioqKZk1B23333Zu8RlNtjQjmzp3L/vvvn49mN0tRB0CSKoDbgDsi4qc56QJulDQsIi4EngbG70hd\nEVEr6SZg7Hacfhnwtx2p38zMzMx2vi1tW7169Wo6duyY1/pGjx7NuHHjmDx5Ml26dOGdd96hR48e\nLFy4kAkTJjB//nzq6up2uJ4xY8Ywa9Yszj///E1T4A4//HAmTpzIlClTiAjuvPNObrzxxjy8q+Y7\n6qijmDlzJjNnzkQSixYtYsiQIRxxxBHccsstjB49mueee44lS5bkrc5inwI3BaiLiNtzE9Ozfb4J\nfE3S0RGxPiJWFKSFWXvejIjaQtVvZmZmZq1Tv379mDp1KiNHjmTQoEFMnjyZSZMm8eCDDzJo0CAe\ne+yxzUZWtseMGTN44IEHGDBgAMOGDWPp0qUMHTqUiRMnMnz4cEaMGMGZZ57JkCFD8vCumu+iiy6i\nrq6OgQMH0q9fPy666CIAzjnnHGpra+nbty8XX3wxw4YNy1udymKF4pNGf94CTomIe5oo82tgHXAh\n8H8i4kRJbYAvAnsC7YHBwABgfEQsTeftDxwDLE55syJinaQewA3AdOBTwL8CV0fEDem8/YBTUvX9\ngROACuDzQLeIuLyRNp4FnAVQVdV12B133N6wiJWo2traTTunWOlzf5cP93V5cX8Xv06dOtGnT59m\nld2wYQMVFRU7uUW2rZYvX87777//kbRRo0YtjIiDGitfzFPg+pIFMcu3UOZVYDQwEDg4pX0SOJds\nWty5EbFB0rnAGcAFqcxPgRMi4jVJbYHfSFoJ/BDoCbwSEV+WtCewCLghlbseGJWCpT8AewMfAp8B\nXmisgRExG5gNsE+vPlFdXb3tn4QVpQULFuD+Lh/u7/Lhvi4v7u/it2zZsmZPa9sZU+Bsx3Xo0GGb\nRq6KeQpc/X+3bGlTgveA1RFxW31CRLwK3A08FhH1+04vbXCdgcDb6fUKoEtEnEa2ycKrEbEkXevd\nnHPaAJNS8DMU+BjQLiLeA36zPW/QzMzMzGxbXHrppQwePPgjX5deemmhm9WqFPMI0PNkoyv9gceb\nKNML+LWrKQQAAAdrSURBVF0zr6ec178EDgEeTN/v39rJKfB5XdJ3yTZmeKuZ9ZqZmZlZAUUE2R5a\nxW/q1KlMnTq10M1oMduznKdoR4AiYjUwFZic1vV8hKS9gGHAVdtx+e8Cp0r6FNnubZs/6alxNwNz\nyYKzT2TNUPstn2JmZmZmhdKhQwdWrVq1XX9IW2FFBKtWraJDhw7bdF4xjwARETMkvQ9cJelbEfE3\nAEl9yHaI+xRQJ+lUYE9JY4HXyEZ1+kt6hmyq278BgyUNAl4Bbgc+ExHL6uuStAfwOaC3pJPIAp2x\nQJWkfycb9fk48CWyKW8PA7OA/5fK7SGpd0S83NT72bWdF9WZmZmZtaTu3buzcuVK3npr65N31q5d\nu81/bNvO1aFDB7p3775N5xR1AAQQETdI6gSMlHQUcBDZyNCkiIi0OcGtwE3ALmS7wh2d8pS2zP7I\nCI+k84CHJb0G1AGrgIuB70XEdEkVaf3Qr/nHWiRS3fXuStfaBXiIbIpd0X/eZmZmZqWkXbt29OzZ\ns1llFyxY0OLbRFv+lcQf5BHxPvBrSQ+QbVN9GXAmsCwich+J+/cG52021impP3AY0D0i1qa0QcCV\nETE2nbeh4XlbaFv9o3uDLPgyMzMzM7MCKdo1QI2JiLURcRLw38B1km6TNLaxNUJbcBqwuD74SZYB\nC/LYVDMzMzMzK4CSGAFqKCLmAfMkdQf6AF2BN5p5+jTggvSg1XeBjcDuZEGVmZmZmZkVMXnHi9ZD\n0mrgxUK3w1pMFf943pSVPvd3+XBflxf3d3lxfxePT0ZE18YySnIEqIi9GBEHbb2YlQJJT7m/y4f7\nu3y4r8uL+7u8uL9LQ0mtATIzMzMzM9sSB0BmZmZmZlY2HAC1LrML3QBrUe7v8uL+Lh/u6/Li/i4v\n7u8S4E0QzMzMzMysbHgEyMzMzMzMyoYDIDMzMzMzKxsOgFoJSZ+W9KKk5ZKmFLo9tu0k/bOkByQt\nlfS8pK+m9M6SfifppfR9z5QuSd9Lfb5E0tCca30xlX9J0hcL9Z5s6yRVSFok6VfpuKekJ1K//lzS\nLim9fTpenvJ75FzjwpT+oqSjCvNObGskfUzSHEkvSFom6V98f5cmSV9Lv8efk3SrpA6+t0uHpOsk\nvSnpuZy0vN3LkoZJejad8z1Jatl3aFvjAKgVkFQB/AA4GjgQ+HdJBxa2VbYd1gMXRMSBwCHAl1M/\nTgHui4h9gfvSMWT9vW/6OguYBdkvYeDbwAhgOPDt+l/E1ip9FViWc/xd4OqI6AO8C5yR0s8A3k3p\nV6dypJ+Rk4B+wKeBH6bfCdb6zAB+ExEHAIPI+t33d4mR1A04DzgoIvoDFWT3qO/t0nEDWZ/kyue9\nPAuYlHNew7qswBwAtQ7DgeUR8UpErANuA44rcJtsG0XEXyLi6fR6NdkfR93I+vKnqdhPgc+l18cB\nP4vM48DHJH0COAr4XUS8ExHvAr/DvzxbJUndgWOBn6RjAaOBOalIw/6u/zmYA4xJ5Y8DbouIv0fE\nq8Byst8J1opI6gQcAVwLEBHrIuI9fH+XqrbArpLaArsBf8H3dsmIiIeAdxok5+VeTnl7RMTjke00\n9rOca1kr4QCodegG/DnneGVKsyKVpkAMAZ4APh4Rf0lZfwU+nl431e/+eSge04FvAhvTcRfgvYhY\nn45z+25Tv6b891N593dx6Am8BVyfpjz+RNLu+P4uORHxGnAFsIIs8HkfWIjv7VKXr3u5W3rdMN1a\nEQdAZnkmqRKYC5wfER/k5qX/DfLe8yVA0r8Bb0bEwkK3xVpEW2AoMCsihgAf8o8pMoDv71KRpjEd\nRxb07g3sjkfpyorv5dLnAKh1eA3455zj7inNioykdmTBz80R8YuU/EYaEid9fzOlN9Xv/nkoDocB\nn5VUQzZtdTTZGpGPpWkz8NG+29SvKb8TsAr3d7FYCayMiCfS8RyygMj3d+kZC7waEW9FRB3wC7L7\n3fd2acvXvfxaet0w3VoRB0Ctwx+BfdMOM7uQLZqcX+A22TZKc76vBZZFxFU5WfOB+t1hvgjclZN+\nWtph5hDg/TT8/lvgSEl7pv+JPDKlWSsSERdGRPeI6EF2z94fEScDDwDjU7GG/V3/czA+lY+UflLa\nSaon2YLZJ1vobVgzRcRfgT9L2j8ljQGW4vu7FK0ADpG0W/q9Xt/XvrdLW17u5ZT3gaRD0s/PaTnX\nslai7daL2M4WEesl/QfZzVQBXBcRzxe4WbbtDgNOBZ6V9ExK+xYwDbhd0hnAn4AJKe8e4BiyhbF/\nA74EEBHvSPq/ZIExwH9FRMPFmtZ6/Sdwm6TvAItIi+bT9xslLSdbfHsSQEQ8L+l2sj+w1gNfjogN\nLd9sa4avADen/6h6heyebYPv75ISEU9ImgM8TXZPLgJmA3fje7skSLoVqAaqJK0k280tn/9Wn0u2\n09yuwK/Tl7Uiyv6TwszMzMzMrPR5CpyZmZmZmZUNB0BmZmZmZlY2HACZmZmZmVnZcABkZmZmZmZl\nwwGQmZmZmZmVDQdAZmZmZmZWNhwAmZmZmZlZ2fj/fZqWss7j6OAAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 936x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "atsiA6zYOzJi",
        "colab_type": "text"
      },
      "source": [
        "An optional parameter *largestN* can be provided to display only the top N bars. For example, the following compares the top 10 cities in terms of the highest newly confirmed counts on 2020–02–05:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B_nJqXavOraK",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "outputId": "30f581ed-5d41-4a62-b105-f1371eb65961"
      },
      "source": [
        "fig = utils.cross_sectional_bar(daily_frm, '2020-02-05', col='new_confirmed', groupby='city_name_en', largestN=10, title='Top 10 cities with the most new confirmed counts on 2020-02-05' )\n",
        "plt.show()"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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2Hrsb8JzMPCwingp8CvhS3f81wI8y831133OAvwe+HRHrA8dl5rZ120ci4gvA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\n8EiSJEkqLQOPJEmSpNIy8EiSJEkqrf8GnuLmWb70bjoAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 936x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5_mNgP4uPF0P",
        "colab_type": "text"
      },
      "source": [
        "## Final Words\n",
        "Above are some basic usages of the toolbox. Hope you find it convenient and helpful to gain a better understanding of recent the coronavirus epidemic. \n",
        "In the next article, I am going use this toolbox to analyze the death rate. You will see that it is not as simple as the widely circulated 2%."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vLE7y8Q8PMPv",
        "colab_type": "text"
      },
      "source": [
        "## Acknowledgement\n",
        "I want to thank my friend David Tian, a Machine Learning engineer, for his helps on the Google Colab setup, and his valuable suggestions. Check out his fun self-driving [DeepPiCar](https://towardsdatascience.com/deeppicar-part-1-102e03c83f2c) blog."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jb5XuKWYPHj_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}